WO2016156936A1

WO2016156936A1 - System and method of ranking points of interest using photograph rating

Info

Publication number: WO2016156936A1
Application number: PCT/IB2015/055386
Authority: WO
Inventors: Artem Andreevich VODOLAZSKY; Renat Rafaelevich NASYROV; Anton Viktorovich SLESAREV
Original assignee: Yandex Europe Ag; Yandex Llc; Yandex Inc.
Priority date: 2015-03-31
Filing date: 2015-07-16
Publication date: 2016-10-06
Also published as: RU2015111646A

Abstract

A system and method of ranking points of interest using photograph rating, the method comprising: receiving a first plurality of parameters of the first point of interest; finding a first photograph, the description parameters and the location parameters of which indicate that it shows a first object and associating it with the first object; receiving a second photograph having a visual resemblance to the first photograph and associating it with the first object; calculating an importance coefficient of the first point of interest based on the quantity of photographs associated with it, and calculating an importance coefficient of the second point of interest based on the quantity of photographs associated with it, and the corresponding quantity of photographs associated with the first point of interest includes the first photograph and the second photograph associated with the first point of interest; assigning a higher rating to the first point of interest, with which more photographs are associated.

Description

SYSTEM AND METHOD OF RANKING POINTS OF INTEREST USING

PHOTOGRAPH RATING

CROSS-REFERENCE

[1] The present application claims priority to Russian Patent Application No. 20151 1 1646, filed March 31 , 2015, entitled "CHCTEMA H CIIOCOE PAHJKHPOBAHKH TOHEK HHTEPECA C HCIIOJIb30BAHHEM ΦΟΤΟΡΕΗΤΗΗΓΑ" the entirety of which is incorporated herein.

FIELD OF THE TECHNOLOGY

[2] The present technology relates to a system and method of ranking points of interest using photograph rating.

BACKGROUND

[3] Modern information technologies provide users with multiple ways of exploring attractions. Often, tourists can use applications installed on their mobile devices, which facilitate the exploration of nearby objects.

[4] For example, the computer program "i-Guide: offline routes" (rus. "i-3KCKypcoBO : ocjD aHH MapuipyTbi") assists with self-guided walking tours of various cities in the world. This application allows tourists to plan a self-guided tour - to choose any of a variety of prepared tour routes through various cities in the world; to make their own route on an electronic device; and to import a pre-planned route. Each route in this application includes lines indicating the route and marks indicating points of interest. Each mark contains information - a photograph and a description. To avoid roaming, this application allows to save a route on an electronic device and follow the route while the device is in an "offline" mode.

[5] Another example is the "TWalk: Paris" (rus. "TWalk: napH:sc") application. This application is available in English and Russian and provides the ability to work offline. This application allows to display the location of a tourist on a detailed map of Paris, and suggests four routes through different parts of the city as well as an additional overview route, with descriptions accompanied by photographs. According to its description of, the application includes " 100 attractions - more than any printed guide".

[6] Yet another example is the "Sightseeing Compass Free" application by IGRASS PTY LTD. This application allows a user to quickly find nearby places of interest, wherever he is located. Upon launching this application, it will automatically show the closest object that is an attraction, indicating the distance thereto, and reducing this distance as the user moves closer to the attraction. This application also provides the ability to switch to a "map" mode and select any attractions the tourist desires. In the "map" mode, all the attractions located nearby are shown to the user.

[7] While in some regions, the quantity of attractions per unit area is relatively small, in other regions the number of attractions near a tourist can be very significant.

[8] In some cases, the compilers of electronic guides do not include with their applications some objects that can be of interest to tourists because they may not be aware that a given object could be of interest. Example of this include objects that travel Agency "Hidden City Tours", supported by the charity fund RAIS, shows to its customers, namely - free city eateries, overcrowded slums and other objects representative of social problems in Barcelona.

SUMMARY

[9] It is an object of the present technology to ameliorate at least some of the inconveniences present in the prior art.

[10] According to a first broad aspect of the present technology, there is provided a method of ranking at least two points of interest from a plurality of points of interest using photograph rating, the method executable at a server, a first point of interest representing a first object, a second point of interest representing a second object, the second point of interest being associated with a second plurality of photographs showing the second object, and each point of interest from the plurality of points of interest being associated with a predefined plurality of parameters of the corresponding point of interest, the method comprises: receiving a first plurality of parameters of the first point of interest, the first plurality of parameters of the first point of interest, including at least one location parameter and at least one description parameter describing the first object represented by the first point of interest; executing a first step of determining a popularity of the first object represented by the first point of interest, including: receiving a first photograph associated with a first plurality of parameters of the first photograph, the first plurality of parameters of the first photograph including at least one location parameter and at least one description parameter; calculating a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest; in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating the first photograph with the first point of interest; executing a second step of the determining of the popularity of the first object represented by the first point of interest, including: receiving a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters of the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest; based on a comparison of the second photograph with the first photograph by using descriptors of characteristic features of an image, determining an indicator of similarity between the second photograph and the first photograph; in response to exceeding the indicator of similarity between the second photograph and the first photograph, associating the second photograph with the first point of interest; calculating an importance coefficient of the first point of interest based on a quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating an importance coefficient of the second point of interest based on a quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph; in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning to the first point of interest a rating higher than to the second point of interest.

[11] In some implementations of the present technology, the method further comprises generating a plurality of points of interest, such that each point of interest from the plurality of points of interest corresponds to a corresponding single object.

[12] In some implementations of the present technology, the generating the plurality of points of interest includes receiving by the server information associated with objects that can potentially be represented by points of interest, including receiving a predefined plurality of parameters of each object from a plurality of objects, and the predefined plurality of parameters includes at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding points of interest.

[13] In some implementations of the present technology, the receiving by the server of information associated with objects that can potentially be represented by points of interest is effected using public data sources.

[14] In some implementations of the present technology, at least one of the receiving the first photograph and the receiving the second photograph is effected using public data sources.

[15] In some implementations of the present technology, the second plurality of parameters of the second photograph includes at least one of: (1) a location parameter, and (2) at least one description parameter.

[16] In some implementations of the present technology, the determining of the indicator of similarity between the second photograph and the first photograph comprises comparing the plurality of parameters of the second photograph and the plurality of parameters of the first photograph.

[17] In some implementations of the present technology, the at least one description parameter of the first object is at least one of a name of an object and a description of an object.

[18] In some implementations of the present technology, the calculating the first proximity coefficient is executed using the at least one location parameter of the first photograph and the at least one location parameter of the first point of interest.

[19] In some implementations of the present technology, the calculating the first proximity coefficient is executed using the at least one description parameter of the first photograph and the at least one description parameter of the first point of interest.

[20] In some implementations of the present technology, at least one description parameter of at least one of the first photograph and the second photograph is a photographer identifier , and while calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, at least one reduction coefficient is used if the quantity of photographs with the same photographer identifier in the first plurality of the photographs associated with the first point of interest exceeds a predefined value.

[21] In some implementations of the present technology, the first photograph is a third plurality of first photographs, the second photograph is a fourth plurality of second photographs, and the determining of the indicator of similarity between the second photograph and the first photograph is effected by comparing each photograph from the fourth plurality of second photographs with at least some of the photographs from the third plurality of first photographs.

[22] In some implementations of the present technology, the method further comprises receiving a user request to provide information associated with any of the first object and the second object, and in response to the receiving of the user request to provide information, generating by the server search results based on a rating of the first point of interest and a rating of the second point of interest.

[23] In some implementations of the present technology, the method further comprises sending the search results by the server to a user electronic device to be displayed to the user.

[24] Another object of the present technology is a server. The server includes a processor. The processor is configured to render the server to execute: receiving a first plurality of parameters of a first point of interest, the first plurality of parameters of the first point of interest including at least one location parameter and at least one description parameter describing a first object represented by the first point of interest; executing a first step of determining a popularity of the first object represented by the first point of interest, including: receiving a first photograph associated with a first plurality of parameters of the first photograph, the first plurality of parameters of the first photograph including at least one location parameter and at least one description parameter; calculating a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest; in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating the first photograph with the first point of interest; executing a second step of the determining the popularity of the first object represented by the first point of interest, including: receiving a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters of the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest; based on a comparison of the second photograph with the first photograph using descriptors of characteristic features of an image, determining an indicator of similarity between the second photograph and the first photograph; in response to exceeding of indicator of similarity between the second photograph and the first photograph, associating the second photograph with the first point of interest; calculating an importance coefficient of the first point of interest based on a quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating the importance coefficient of the second point of interest based on a quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph; in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning to the first point of interest a rating higher than a rating of the second point of interest.

[25] In some implementations of the server, processor is further configured to render the server to generate a plurality of points of interest, such that each point of interest from the plurality of points of interest corresponds to a corresponding single object.

[26] In some implementations of the server, the generating the plurality of points of interest includes receiving by the server of information associated with objects that can potentially be represented by points of interest, including receiving a predefined plurality of parameters of each object from a plurality of objects, and the predefined plurality of parameters includes at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding points of interest.

[27] In some implementations of the server, the receiving by the server of information associated with objects that can potentially be represented by points of interest is effected using public data sources. [28] In some implementations of the server, at least one of the first photograph and the second photograph is effected using public data sources.

[29] In some embodiments of the server, the second plurality of parameters of the second photograph includes at least one of: (1) a location parameter, and (2) at least one description parameter.

[30] In some implementations of the server, the determining of the indicator of similarity between the second photograph and the first photograph comprises comparing the plurality of parameters of the second photograph and the plurality of parameters of the first photograph.

[31] In some implementations of the server, the at least one description parameter of the first object is at least one of a name of an object and a description of an object.

[32] In some implementations of the server, the calculating the first proximity coefficient is executed using the at least one location parameter of the first photograph and the at least one location parameter of the first point of interest.

[33] In some implementations of the server, calculating of the first proximity coefficient is executed using the at least one description parameter of the first photograph and the at least one description parameter of the first point of interest.

[34] In some implementations of the server, at least one description parameter of at least one of the first photograph and the second photograph is a photographer identifier, and while calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, at least one reduction coefficient is used if the quantity of the photographs with the same photographer identifier in the first plurality of the photographs associated with the first point of interest exceeds a predefined value.

[35] In some implementations of the server, the first photograph is a third plurality of the first photographs, the second photograph is a fourth plurality of second photographs, and the determining of the indicator of similarity between the second photograph and the first photograph is effected by comparing each photograph from the fourth plurality of the second photographs with at least some of the photographs from the third plurality of first photographs. [36] In some implementations of the server, the processor is further configured to render the server to receive a user request to provide information associated with any of the first object and the second object, and, in response to receiving the user request to provide information, generate search results based on the rating of the first point of interest and the rating of the second point of interest.

[37] In some implementations of the server, the processor is further configured to render server send the search results to a user electronic device to be displayed to the user.

[38] In the context of the present specification, a "server" is a computer program that is running on appropriate hardware and is capable of receiving requests over a network, and carrying out those requests, or causing those requests to be carried out. The hardware may be one physical computer or one physical computer system but neither is required with respect to the present technology. In the present context, the use of the term "server" is not intended to mean that every task (e.g., received instructions or requests) or any particular task will have been received, carried out, or caused to be carried out, by the same server (i.e., the same software and/or hardware); it is intended to mean that any amount of software elements or hardware devices may be involved in receiving/sending, carrying out or causing any task or request, or the consequences of any task or request to be carried out; and all of this software and hardware can include one server or multiple servers, both of which are included within the term "server".

[39] In the context of the present specification, the expression "information" includes information of any nature and kind whatsoever capable of being stored on a storage device. Thus, "information" includes, but is not limited to, audiovisual works (images, video, audio, etc.), data (map data, location data, numerical data, etc.), text (signs, titles, descriptions, warnings, text messages, etc.), documents, spreadsheets, etc.

[40] In the context of the present specification, the expression "software component" includes software (appropriate to the particular hardware) that is both necessary and sufficient to achieve the specific function(s) being referenced.

[41] In the context of the present specification, the expression "object", which can be represented on a map (map material) by a point of interest, includes an object that can have geographical coordinates and that can be shown on a photograph. As non-limiting examples, the object can be a building, structure, facility, another artifact, natural object or a combination thereof. An object can be a complex object, the individual elements of which are, or can potentially be, separate objects (e.g., the Moscow Kremlin and the Spasskaya Tower of the Moscow Kremlin). Objects that can be represented on a map by a point of interest can be attributed to a particular type of object, for example, using the heading. Objects can be described. The description of objects can be vary depending on the type of object.

[42] In the context of the present specification, the expression "point of interest" (POI) includes a mark on a map, which indicates an object or group of objects. A point of interest can include information associated with the object(s), for example, name, type, address, contact information, photograph and characteristic points of an image (e.g., SURF descriptors). A point of interest can include information about the object(s) in, for example, a point of interest card, which can be a structured block of information. A point of interest card can have a particular structure determined by a predefined set of facts that should be or can be stored in the point of interest card during the process of generating the card. The structure of the point of interest card can be determined by the plurality of parameters that can characterize the corresponding object.

[43] In the context of the present specification, the expression "computer information storage medium" or simply "computer readable medium" is are intended to include media of any nature and kind whatsoever, including, without limitation, RAM, ROM, disks (CD-ROMs, DVDs, floppy disks, hard drivers, etc.), USB keys, solid state-drives, tape drives, etc. A plurality of components may be combined to form the computer information storage medium, including two or more media components of the same type and/or two or more media components of different types.

[44] In the context of the present specification, a "database" is any structured collection of data, irrespective of its particular structure, database management software, or computer hardware on which the data is stored, implemented or otherwise rendered available for use. A database may reside on the same hardware as the process that stores or makes use of the information stored in the database, or it may reside on separate hardware, such as a dedicated server or plurality of servers.

[45] In the context of the present specification, the words "first", "second", "third" etc. have been used as adjectives only for the purpose of allowing for distinction between the nouns that they modify from one another, and not for the purpose of describing any particular relationship between those nouns. Thus, for example, it should be understood that, the use of the terms "first point of interest" and "third point of interest" is not intended to imply any particular order, type, chronology, hierarchy or ranking (for example) of/between the points of interest, nor is their use (by itself) intended to imply that any "second point of interest" must necessarily exist in any given situation.

[46] Implementations of the present technology each have at least one of the above mentioned objects and/or aspects, but do not necessarily have all of them. It should be understood that some aspects of the present disclosure that have resulted from attempting to achieve the above mentioned object may not satisfy this object, and/or may satisfy other objects not specifically recited herein.

[47] Additional and/or alternative features, aspects, and advantages of embodiments of the present disclosure will become apparent from the following description, the accompanying drawings, and the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[48] For a better understanding of the present technology, as well as other aspects and further features thereof, reference is made to the following description which is to be used in conjunction with the accompanying drawings, where:

[49] Fig. 1 is a schematic representation of the implementation of a network computer system implemented in accordance with non-limiting embodiments of the present technology.

[50] Fig. 2 is a schematic image of a map.

[51] Fig. 3 is a schematic block diagram of the method 300, implemented on the server depicted in Fig. 1 in accordance with non-limiting embodiments of the present technology.

DETAILED DESCRIPTION

[52] In Fig. 1, there is depicted a schematic diagram of various computer systems 100 which are connected to each other via a communication network 110. It is to be expressly understood that the computer systems 100 are depicted as the illustrative implementations of the present technology. Thus, the description thereof that follows is intended to be only a description of illustrative examples of the present technology. This description is not intended to define the scope or set forth the boundaries of the present technology. In some cases, what are believed to be helpful examples of modifications to the computer systems 100 may also be described below. This is done merely as an aid to understanding, and, again, not to define the scope or set forth the boundaries of the present technology. These modifications do not constitute an exhaustive list, and, as a person skilled in the art would understand, other modifications are possible. Further, where no examples of modifications have been set forth, it should not be understood that no modifications are possible and/or that what is described is the sole manner of implementing that, element of the present technology . As a person skilled in the art would understand, this is likely not the case. In addition, it is to be understood that the computer systems 100 may in certain instances provide a relatively simple implementation of the present technology, and where this is the case, it has been presented in this manner as an aid to understanding. As a person skilled in the art would understand, various implementations of the present technology may be of greater complexity.

[53] The computer systems 100 include a server 102. The server 102 may be implemented as a conventional computer server. In an example of an implementation of the present technology, the server 102 may be implemented as a Dell™ PowerEdge™ Server running the Microsoft™ Windows Server™ operating system. Needless to say, the server 102 can be implemented in any other suitable hardware and/or software and/or firmware or a combination thereof. In the depicted non-limiting implementation of present technology, the server 102 is a single server. In alternative non-limiting implementations of the present technology, the functionality of the server 102 may be divided amongst and implemented via multiple servers.

[54] In the given implementation of the present technology, the server 102 is controlled and/or managed by a map service provider such as, for example, the provider of Yandex. Maps™. In alternative implementations of the present technology, the server 102 can access a map service provided by a third-party provider.

[55] The server 102 includes an information storage medium 104 that can be used by the server 102. Generally, the information storage medium 104 can be implemented as a medium of any nature and kind whatsoever, including RAM, ROM, disks (CD-ROMs, DVDs, floppy disks, hard drivers, etc.), USB keys, solid state-drives, tape drives, etc., as well as a combination thereof.

[56] Implementations of the server 102 are well known in the art. Thus, suffice it to note that the server 102 includes, inter alia, a network communication interface (such as a modem, a network card, etc.) (not shown) for two-way communication over the communications network 110, and a processor (not shown) connected to the network communication interface, the processor being configured to execute various routines, including those described hereinbelow. To that end, the processor may store or have access to computer readable instructions stored on the information storage media 104, which, when executed, cause the processor to execute the various routines described herein.

[57] The medium storage 104 of the server 102 is intended to store data, including computer- readable instructions and databases.

[58] In particular, the storage medium 104 of the server 102 stores databases 106, which store map material.

[59] The databases 106 store the information associated with a plurality of objects which can have geographical coordinates and be captured on a photograph.

[60] For example, in some implementations of the present technology, the plurality of objects can represent a plurality of attractions and places of interest for tourists in Moscow, Russia. For example, objects of the given plurality of objects can be the Bolshoi Theater, the <monument of A. M. Ostrovsky, St. Basil's Cathedral, the Spasskaya Tower of the Moscow Kremlin, the Troitskaya Tower of the Moscow Kremlin and others. In other implementations of present technology, the plurality of objects can additionally or alternatively include other objects, such as public transport objects, catering facilities and/or places of trade and any other objects that have geographical coordinates and can be photographed. For example, this can be the Starbucks coffee shop located at Paveletskaya Square in Moscow or the Shokoladnitsa coffee shop also located at Paveletskaya Square, or any other object that can be captured on a photograph. Objects can be presented on map material by points of interest.

[61] The databases 106 can store information about the plurality of objects by storing information associated with points of interest. Thus, each point of interest is associated with a predefined plurality of parameters that can be grouped into a point of interest card. The point of interest and the point of interest card are generated by the server 102 by executing program instructions stored on the storage medium 104, and are then stored in the databases 106.

[62] The databases 106 can store points of interest and point of interest cards. A point of interest card is a structured block of information describing a corresponding object. This structured block of information can be stored as a predefined plurality of parameters. The point of interest card is generated by the server 102 as a result of executing program instructions stored on the storage medium 104, and is then stored in the databases 106.

[63] A point of interest card can have a particular structure determined by a predefined set of facts, which must be collected and stored in a point of interest card during the process of generating a point of interest card by the server 102. The specific structure of a point of interest card can be determined in accordance with the corresponding object type. For example, the set of facts added to a point of interest card representing an object of trade can be different from the set of facts added to a point of interest card representing an attraction.

[64] The storage medium 104 of the server 102 also stores computer-readable instructions that manage the control, updating, populating and modification of the databases 106. More specifically, the computer-readable instructions stored on the information storage media 104 allow the server 102 to receive (to update) information associated with the objects via the communication network 110, to store information associated with the objects, including information associated with corresponding points of interest, in the databases 106, to change the description of the location and/or characteristics of objects and to remove certain objects from the map by removing them from the databases 106.

[65] More specifically, the execution of the computer-readable instructions allows the server 102 to receive information associated with objects that can potentially be represented by points of interest, including the receiving of the predefined plurality of parameters of each object from the plurality of objects, wherein the predefined plurality of parameters can include at least one location parameter and at least one description parameter. The execution of these computer- readable instructions also allows the server 102 to assign corresponding parameters to the corresponding points of interest (including corresponding points of interest cards if any have been generated) and to store points of interest (including point of interest cards if any have been generated) in the databases 106.

[66] The computer-readable instructions stored on the information storage media 104 allow the server 102 to receive information associated with objects that can potentially be represented by points of interest from public data sources. For example, they may allow the server 102 to search and receive photographs available on the Internet that show an object. The search can be performed using search engines, including specialized search engines allowing to search for similar images.

[67] The computer-readable instructions stored on the information storage media 104 allow the server 102 to receive information associated with objects that can potentially be represented by points of interest from proprietary data sources. For example, the owner of the server 102 can independently determine the geographical coordinates of objects - attractions in Moscow - on the spot and independently record the data obtained in point of interest cards and store the data in the databases 106.

[68] Alternatively or additionally, the computer-readable instructions stored on the information storage media 104 allow the server 102 to receive information associated with objects that can potentially be represented by points of interest from an entity interested in publishing information associated with an object. For example, the server 102, being controlled and/or managed by a map service provider, may provide any person with the opportunity to mark objects on maps and make descriptions of these objects. For example, such a person can be any user (not shown) who accesses a map service provider using a browser and downloads from the server 102 to his electronic device the map of a specific area to be shown on the display of the device, marks on the map shown on the display a newly-erected monument, specifies its name and provides a brief description thereof.

[69] The information storage media 104 also stores computer- readable instructions allowing to calculate SURF (Speed Up Robust Features) descriptors and to compare photographs in order to identify the visual similarity thereof.

[70] The information storage media 104 also stores computer-readable instructions providing the possibility to receive from the electronic device 112, via the communication network 110, the requests of the user 111 to provide the list of objects in a certain area of space, receive from the database 106 information associated with objects, stored in the databases 106, corresponding to the area of space that the user 111 is interested in, and send to the electronic device 112, via the communication network 110, the instructions to show one or more points of interest on a map on the display 118 of the electronic device 112.

[71] In the given implementation of the present technology, the server 102 may be configured to execute one or more searches in response to a search query (including one using the map service) received from the electronic device 112 connected to the server 102 via the communication network 110. The server 102 is also configured to transmit to the electronic device 112 a search result to be displayed to the user 111 on the display 118of the electronic device 112 via the browsing interface 116. These functions are well known in the art and will thus not be described here.

[72] The server 102 is connected to the communication network 110 via a communication link (not numbered). In some non-limiting embodiments of the present technology, the communication network 110 can be implemented as the Internet. In other embodiments of the present technology, the communication network 110 can be implemented differently, such as any wide-area communication network, local-area communication network, private communication network, etc.

[73] How the communication link is implemented is not particularly limited and will depend on which devices are connected to the communication network 110. As a non-limiting example, the connection of the server 102 to communication network 110 can be implemented via a wired connection (such as an Ethernet based connection). At the same time, other devices can also be connected in other ways. In the examples where the connected device is implemented as a wireless communication device (e.g. the electronic device 112 implemented as a smartphone), the connection can be implemented as a wireless communication network (such as, but not limited to, a 3G communications network link, a 4G communications network link, Wireless Fidelity or WiFi® for short, Bluetooth®, etc.). In the examples where the device 102 is implemented as a desktop computer, the communication link can be either wireless or wired (such as an Ethernet based connection). [74] It should be expressly understood that various implementations of the server 102, the electronic device 112 and the communication links for the connection to the communication network 110 are provided for illustration purposes only. As such, those skilled in the art will appreciate details of other specific embodiments of the server 102, the electronic device 112 and the communication links for the connection to the communication network 110. Thus, by no means are examples provided hereinabove meant to limit the scope of the present technology.

[75] The server 102 can be connected via the communication network 110 with the electronic device 112. The electronic device 112 is typically associated with the user 111. The user 111 is a person interested in receiving information about objects having spatial coordinates. In the given implementation of the present technology, the user 111 can be a tourist who is searching for attractions in the center of Moscow using the electronic device 112.

[76] In alternative implementations of the present technology, the user 111 can search for objects of another category. For example, as a non-limiting example, the user 111, amongst numerous potential examples, can be a man looking for a coffee shop in the area of Pavel etskaya Square in Moscow, Russia.

[77] It should be noted that the fact that the electronic device 112 is associated with the user 111 does not suggest or imply any mode of operation, such as a need to log in, a need to be registered, etc.

[78] The implementation of the electronic device 112 is not particularly limited, but as an example, the electronic device 112 may be implemented as a personal computer (desktop, laptop, netbook, etc.), a wireless communication device (cell phone, smartphone, tablet, etc.) as well as network equipment (router, switch or gateway). The electronic device 112 depicted in Fig. 1 is implemented as an Apple™ iPhone 5S smartphone running the iOS7 operation system, with Bluetooth™, Wi-Fi™, 3G, LTE, GPS and GLONASS.

[79] The electronic device 112 also includes an information storage medium 114. Generally, the information storage medium 114 can be implemented as a medium of any nature and kind whatsoever, including RAM, ROM, disks (CD-ROMs, DVDs, floppy disks, hard drivers, etc.), USB keys, solid state-drives, tape drives, etc., as well as a combination thereof. In electronic device 112, schematically depicted in Fig. 1, the information storage medium 114 is implemented as a flash drive with 16 GB of memory.

[80] The information storage medium 114 can store user files and program instructions. More specifically, the storage medium 114 can store software which executes functions of the browser 116. Generally, the purpose of the browser 116 is to enable the user 111 to upload the files to the electronic device 112 via communication network 110 from the server 102 and to show the uploaded images and/or the text on the display 118.

[81] How the browser 116 is implemented is not particularly limited. As non-limiting examples, the browser 116 can be implemented as Yandex™ browser, Google Chrome™, Internet Explorer™, various mobile search applications, etc. On the electronic device 112, the browser 116 is implemented as the mobile browser Yandex™. It should be expressly understood that any other commercially available or proprietary application can be used for implementing non-limiting embodiments of the present technology.

[82] The electronic device 112 also includes a display 118 which is a 4" touchscreen, with a resolution of 640x1136 allowing to provide video information to the user 111, and which can be used as an information input device. As such, the user 111 has the ability to view various objects on the display 118, in the interface of the browser 116 of the electronic device 112, such as attractions marked by points on a map or text information associated with attractions, etc. Moreover, the user 111 can make requests to provide information associated with objects by entering a query using a touchscreen.

[83] Fig. 2 is a schematic image of a map 200.

[84] The map 200 displays an area in the center of Moscow that is adjacent to the intersection of Petrovka Street (not numbered) and Teatralniy Lane (not numbered). In the immediate proximity of this intersection numerous of buildings are located, namely monuments of architecture, including a building 202 of the Bolshoi Theater, the facade of which faces the Teateralnaya Square 206. The building 202 is the first object.

[85] In addition to the building 202, many other attractions are located in the given area. As another non-limiting example, -there is a monument 204 of A. M. Ostrovsky. The monument 204 is the second object. [86] From Teatralnaya Square 206, there is a view of the building 202 that allows users to take photos of the facade of the building 202 from the Teatralnaya Square 206, including from the point 208.

[87] Persons engaged in photography (photographers) can use their cameras, mobile phones, or other suitable equipment. It is not important, , whether a photograph was taken by amateur or professional photographers for the purposes of the description of the present technology.

[88] Some cameras, mobile phones and other devices that have a built-in GPS receiver, are able to geotag photographs. For example, geotagging is provided by the Canon PowerShot SI 10 camera, the Sony Alpha SLT-A65 camera, the Sony Alpha SLT-A77 smartphone, the Apple iPhone 5S smartphone and others. At the same time, some cameras, mobile phones and other devices may not include the geotagging feature or this feature can be disabled. Accordingly, some photographs will have geotags and others will not.

[89] Photographers can also upload photographs onto the Internet. A photograph can be uploaded either directly from the device with which it was taken (not shown) or from a computer (not shown). Some photographs uploaded to the Internet will have geotags while others will not.

[90] When uploading photographs to a webpage on the Internet, photographers can include explanations thereto. For example, when uploading a photograph of the facade of the building 202 of the Bolshoi Theater, the photographer can include the following commentary with the uploaded photograph: "Today we went to the Bolshoi Theater to see the Nutcracker". If another photographer uploads from his desktop computer a photograph of another object - the monument 204 of A. M. Ostrovsky - onto his personal webpage, he can pre-save the photograph as a file named ostrovskiy.jpg and, when placing it, choose the option that allows the display of the text "The Monument of Alexander Ostrovsky" in place of the image if the image cannot be shown to the user 111 for some reason.

[91] Typically, photographers take photographs of objects that are interesting to them. As such, the quantity of photographs of a particular object that have been uploaded onto the Internet allows the server 102 to generate a photograph rating of that object. For example, there are more photographs on the Internet of Leonardo da Vinci's "Mona Lisa" than photographs of Paul Delaroche's "Young Christian Martyr", which is also exhibited in the Louvre. Hence, the photograph rating of the "Mona Lisa" can be considered higher than the photograph rating of the "Young Christian Martyr". The object with the higher photograph rating is considered to be more popular.

[92] Photographs of the same object on the Internet can differ from one another. One of such differences that had already been mentioned above is the presence or absence of geotagging. Other differences may be due to the angle from which the photograph of the object was taken. For example, a child may take photographs of the building 202 from a lower height than an adult photographer. A photographer can take a photograph of the building 202 from either directly in front of the center of the object or from the left of the center of the building 202 or from the right of the center of the building 202 (e.g., at the point 208). The photograph can be taken from different distances (for example, from any point within the Teatralnaya Square 206). The photograph can be taken in different seasons, at different times of day, in different lighting conditions, using different filters, etc.

[93] Fig. 3 is a schematic flowchart of the method 300 implemented at the server 102, schematically depicted in Fig. 1, the method being implemented in accordance with non- limiting embodiments of the present technology

[94] The method 300 is a method of ranking at least two points of interest from a plurality of points of interest using a photograph rating. When ranking at least two points of interest from a plurality of points of interest using a photograph rating, the importance coefficient of the given points of interest is determined based on the quantity of photographs available on the Internet and accessible by the server 102 in which the objects represented by the given points of interest appear. The greater the quantity of photographs of the given object that will be located by the server 102, the higher the rating of the corresponding object will be. The increase of the rating can be directly proportional to the quantity of photographs located or can be expressed as a function of various factors (e.g., photographer identification) and where the increase of the rating is not directly proportional to the quantity of photographs of the object located.

[95] The method 300 begins at step 304.

[96] Step 304 - receiving a first plurality of parameters of a first point of interest [97] In the given implementation of the present technology, each point of interest from the plurality of points of interest is associated with a predefined plurality of parameters describing the corresponding object. For example, in the given implementation of the present technology, the first object is the building 202 of the Bolshoi Theater, and the second object is the monument 204 of A. M. Ostrovsky.

[98] In this embodiment of the present technology, at step 304, the server 102 receives from the databases 106 the first plurality of parameters of the first point of interest, and the first point of interest is the building 202. The first plurality of parameters of the first point of interest describes the building 202.

[99] As would be appreciated by those skilled in the art, in alternative implementations of the present technology, the first object can be another object, either created by nature or artificially. For example, the first object can be the Statue of Roland located in the Market Square of Bremen (Germany), or Bremen Town Hall, also located in the Market Square of Bremen, or any other object.

[100] In the given implementation of the present technology, the predefined plurality of parameters describing the building 202 of the Bolshoi Theater are stored in the corresponding first point of interest card.

[101] In the given implementation of the present technology, prior to the server 102 executing the steps of the method 300, the server 102 generated the plurality of points of interest, such that each point of interest corresponds to a corresponding single object. Thus, as a result of the implementation of such generation, the first point of interest has been generated with respect to the building 202 of the Bolshoi theater.

[102] The generating the plurality of points of interest by the server 102 includes receiving by the server 102 information associated with an object - the building 202 - that can potentially be represented by a point of interest, including receiving the predefined plurality of parameters of that object from the plurality of objects, wherein the predefined plurality of parameters comprises at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding point of interest. [103] In the given implementation of the present technology, before the server 102 executes the steps of the method 300, the server 102 generates the plurality of points of interest and the corresponding points of interest cards. To this end, the server 102 can receive data about the corresponding object from any available data source, including a public data source. A public data source can be any external data source that is available for receiving information associated with the object by the server 102, including by receiving transmissions via the communication network 110 from various hosts. For example, public data sources can be various webpages and websites, including online encyclopedias (such as Wikipedia™), social network websites (such as Facebook™), official websites of objects (such as Bolshoi Theater website), photohosting websites (such as Flickr™), websites of tourism service providers and catering service providers or any other webpages and websites.

[104] The generating of the plurality of points of interest and point of interest cards includes receiving by the server 102 information associated with the object. In a significant amount of cases, information associated with the same object can be available from various sources. For example, if the server 102 receives information from the Internet, the information associated with the object can be available on numerous websites concurrently. In such case, the server 102 determines the priority of the source and receives the information associated with the object from an available source having the highest priority. In an alternative implementation of the present technology, the server 102 receives information associated with the object from numerous available sources and then selects the information from the source with the highest priority or from several sources with the highest priority. Evaluating the priority of data sources can be executed in any suitable manner. For example, the source having the highest priority can be the source that appears first in the Yandex search engine in response to a search query containing the name of the object.

[105] Alternatively or additionally, when searching for relevant sources, the highest priority can, for example, be given first to online encyclopedias, followed by official websites, and finally all other websites. Furthermore, when searching for information associated with an object belonging to a certain category, the highest priority can be given to specialized sites. For example, when receiving information associated with orthodox cathedrals, priority can be given to the website sobory.ru. [106] When the most significant source of information associated with the object has been identified, the server 102 receives the information required to complete the location parameters and description parameters from this source. If the source having the highest priority does not contain any information required to generate one or more parameters, the corresponding information can be received from sources of less significance following the source with the highest priority. In some implementations of the present technology, the information associated with the object that will be associated with the point of interest (e.g., by including it in the card of the corresponding point of interest) can also include specially aggregated information (e.g., specially prepared by experts for association with a certain point of interest).

[107] In various implementations of the present technology, the quantity of parameters contained in a point of interest card and stored in the databases 106 can vary.

[108] In the present implementation of the present technology, each point of interest card includes: (1) a group of description parameters, and (2) a location parameter.

[109] In the given implementation of the present technology, the only location parameter is the geographical coordinates of the object. For example, the geographical coordinates of the Bolshoi Theater building are: 55°45'37" N 37°37'07" E.

[110] In alternative implementations of the present technology, a location parameter can, as a non-limiting example, be an address of an object. Thus, the address of the Bolshoi Theater building is: Russia: Moscow, Teatralnaya Square, 1. In some alternative implementations of the present technology, there can be more than one location parameter (e.g., geographical coordinates and address).

[I l l] Thus, for example, the point of interest card generated in respect to the building 202 of the Bolshoi Theater can include the following description parameters: Title: "Bolshoi Theater". Description: "Twice awarded the Lenin Order, Academic Bolshoi Theater of the Russian Federation (GABT), or simply Bolshoi Theater - one of the largest theaters in Russia and one of the most significant theaters of opera and ballet in the world. The complex of theater buildings is located in the center of Moscow, on Teatralnaya Square". Photograph - photograph of the facade of the Bolshoi Theater and SURF descriptors of this photograph, calculated by the server 102. Contact information: "Tel. +7 495 455-55-55". Hyperlink to the website: «https ://ru. wikipedia. org/wiki/BonbiiiOH_TeaTp» .

[112] In alternative implementations of the present technology, the description parameters can, additionally or alternatively, be any other parameters describing the object.

[113] At step 304, the server 102 receives from the databases 106 the first plurality of parameters of the first point of interest, the first plurality of parameters of the first point of interest including at least one location parameter and at least one description parameter describing the first object represented by the first point of interest.

[114] When the server 102 accesses the databases 106 in order to receive the first plurality of parameters of the first point of interest, the specified parameters, in this implementation of the present technology, are already stored in the databases 106. As such, the server 102 receives from the databases 106 information that had previously been stored in the databases 106 in a structured manner.

[115] Thus, for example, the following description parameters can be received from the point of interest card generated in respect of the building 202 of the Bolshoi Theater. Title: "Bolshoi Theater". Description: Twice awarded the Lenin Order, Academic Bolshoi Theater of the Russian Federation (GABT), or simply Bolshoi Theater - one of the largest theaters in Russia and one of the most significant opera and ballet theaters in the world . The complex of theater buildings is located in the center of Moscow, on Teatralnaya Square". Photograph - photograph of the facade of the Bolshoi Theater and SURF descriptors of the photograph, calculated by the server 102. Contact information: "Tel. +7 495 455-55-55". Hyperlink to the website: «https ://ru. wikipedia. org/wiki/BojibiiiOH_TeaTp» .

[116] From the point of interest card generated in respect of the building 202 of the Bolshoi Theater, a location parameter can be obtained, namely: the geographical coordinates of the Bolshoi Theater: 55°45'37" N 37°37'07" E.

[117] Next, the method 300 proceeds to step 306. [118] Step 306 - receiving a first photograph associated with a first plurality of parameters of the first photograph, including at least one location parameter and at least one description parameter

[119] In the context of the present technology, the term "photograph" means an image obtained as a result of the photographing process. A photograph can be analog or digital. A photograph can be analyzed by the server 102. In order for the server 102 to process an analog photo, the analog photograph can be previously converted into a digital photograph. A photograph can be associated with description parameters and location parameters. Description parameters may include, for example, the name of the file containing the photograph; the description of the photograph on the webpage on which the photograph is posted; the text that may be displayed to the user on the webpage when showing the photograph itself to the user is impossible; the text of a hyperlink leading to the photograph, etc. A location parameter may be a geotag associated with the photograph.

[120] At step 306, the server 102 receives the first photograph associated with the first plurality of parameters of the first photograph, including at least one location parameter and at least one description parameter. Generally speaking, at step 306, the server 102, using a search engine, can find photographs on the Internet that were taken in the immediate vicinity of the objects. The identification of such photographs is possible through a conventional photograph search by using a search engine to conduct the corresponding search query, and by subsequent comparison of the geographical coordinates of photographs and the geographic coordinates of objects. The server 102 can use the text information contained in the description parameters of the corresponding object as a search query. The slight discrepancy between the geographic coordinates and the location where the photograph was taken can be explained by the fact that photographs of large objects are taken from some distance from such objects. In some cases, the geographical coordinates can match (e.g., in case where photos are taken inside an object).

[121] In the given implementation of the present technology, the server 102 receives the first photograph from any source on the Internet. In alternative implementations of the present technology, the potential sources of the first photograph can vary. As non-limiting examples of alternative implementations of the present technology, the server 102 may receive the first photograph exclusively from social networks (e.g., from the Facebook™, Odnoklassniki™ and Vkontakte social networks) or exclusively from specialized websites (e.g., from the Tripadvisor™ websites), or from other sources.

[122] In the given implementation of the present technology, the first photograph received by the server is a file in the JPG format that contains the following information: the name of the file

- IMG_1669.JPG, the photographing date - 2015-02-26 14:27, file size - 1.72 MB, author - SG, size - 3264 x 2448, width - 3264 pixels, height - 2448 pixels, horizontal resolution - 72 ppt, vertical resolution -72 ppt, color depth - 24, presentation colors - sRGB, camera - iPhone 5, focus

- F/2.4, exposure time - 1/20 seconds, ISO speed - ISO 125, focal length - 4 mm. Along with the first photograph, the server 102 receives the information related to the first photograph that has been posted on the webpage on which the first photograph is located, namely the text "Today we went to the Bolshoi Theater to see the Nutcracker". This information contained in the specified file and the text beneath the photograph constitutes description parameters of the first photograph. The geotag of the received first photograph corresponds to the geographical coordinates 55°45'35" N, 37°37'10" E, which correspond to the geographic coordinates of the point corresponding to the Teatralnaya Square 206 in Fig. 2. The geotag of the received firth photograph is a location parameter of the first photograph.

[123] Step 308 - calculating a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest

[124] At step 308, the server 102 calculates the first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest representing the first object - the building 202 of Bolshoi Theater.

[125] The first proximity coefficient is a coefficient showing the degree of probability that the first photograph depicts the first object. Thus, if the first proximity coefficient is less than a certain predefined threshold value of proximity, it is considered that the first photograph does not show the first object in respect of which the first proximity coefficient was calculated. The criteria for establishing the certain predefined threshold value of proximity will be described at step 312. [126] To calculate the first proximity coefficient, the server 102, using the location parameter of the first object and the location parameter of the first photograph, determines the distance between points defined by the geographic coordinates of the first point of interest - the building 202 of the Bolshoi Theater, and the geographic coordinates of the point 208, where the first photograph was taken. The geographic coordinates of the point 208, where the first photograph was taken, are determined by using the location parameter (geotag) associated with the first photograph. In the given case, the geographical coordinates of the point 208 correspond to 55°45'35" N. 37°37'10" E. The geographic coordinates of the first point of interest— the building 202 of the Bolshoi Theater - match 55°45'37" N. 37°37'07" E (the location parameter of the first point of interest).

[127] In the case when the calculated distance does not exceed a predefined maximum value, the server 102 continues to implement the calculation of the first proximity coefficient using at least one description parameter of the first photograph and at least one description parameter of the first object. The maximum value of the distance is determined based on the distance from which it is possible to take good quality photographs of the object. If the calculated distance exceeds the predefined maximum value, the server 102 determines that the first proximity coefficient equals zero.

[128] In the given implementation of the present technology, the maximum value of the distance is 450 meters (in alternative implementations of the present technology, the maximum value of the distance can be more or less than 450 meters). The server 102 determines that the distance between the point 208 (the point from which the first photograph was taken) and the building 202 of the Bolshoi Theater does not exceed 450 meters. As such, the server 102 continues implementing the calculation of the first proximity coefficient using at least one description parameter of the first photograph and at least one description parameter of the first object. In the given implementation of the present technology, the server 102 compares each description parameter of the first object with each description parameter of the first photograph and checks for the presence of full or partial matches between the text in the description parameters of the first photograph and the first object.

[129] The results of the comparing show that the part of the text reading "Today we went to the Bolshoi Theater to see the Nutcracker", which is one of the description parameters of the first photograph, partially matches the text in some description parameters of the first object. Namely: in the name of first object ("Bolshoi Theater"), in the description of the first object ("Twice awarded the Lenin Order, the Academic Bolshoi Theater of the Russian Federation (GABT), or simply Bolshoi Theater - one of the largest theaters in Russia and one of the most significant opera and ballet theaters in the world. The complex of theater buildings is located in the center of Moscow, on Teatralnaya Square"), and in the hyperlink to the first object («https://ru.wikipedia.org/wiki/BojibiiiOH_TeaTp»), the words "Bolshoi" and "Theater" are present.

[130] In the given implementation of the present technology, the presence, frequency and quality of matches, along with the distance between the point 208 and the building 202, determine the value of the proximity coefficient. The value of the proximity coefficient is directly proportional to the quantity, frequency and quality of matches, and inversely proportional to the distance between the objects. The quality of matches in the given implementation of the present technology includes the presence of a match between meaningful words. Meanwhile, prepositions, conjunctions and numerals (except phone numbers) are considered insignificant words.

[131] Next, the method 300 proceeds to step 312.

[132] Step 312 - in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating the first photograph with the first point of interest

[133] At step 312, in response to the first proximity coefficient exceeding the predefined threshold value of proximity, the server 102 associates the first photograph with the first point of interest.

[134] The threshold value of proximity can be set at any suitable value.

[135] In the given implementation of the present technology, the threshold value of proximity can be determined to: (a) filter out any photographs that were taken from further than 450 meters from the corresponding object, and (b) filter out any photographs that are located within 450 meters of the object, if a quantity of matching significant words in the description of the photograph constitutes less than 80% when there are five or more significant words present in the description of the photograph, and if the quantity of matching significant words in the description of the photograph constitutes less than 100% there are less than five significant words in the description of the photograph.

[136] In alternative implementations of the present technology, the threshold value of proximity can be determined in any other suitable manner providing the selection of the first photograph at the first step of determining the popularity of an object with high accuracy and low probability of error.

[137] If the first proximity coefficient does not exceed the predefined threshold value of proximity, the server 102 does not effect associating the corresponding photograph with the first point of interest.

[138] Next, The method 300 proceeds to step 314.

[139] Step 314 - receiving a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters from the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest.

[140] At step 314, the server 102 can search the Internet for the second photograph using one or more type of searches. In alternative implementations of the present technology, a plurality of second photographs can be received as a result of such a search.

[141] The server 102 receives the second photograph associated with the second plurality of parameters of the second photograph, and at least some parameters from the second plurality of parameters of the second photograph differ, at least in part, from the corresponding parameters of the first plurality parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest.

[142] In the given implementation of the present technology, in step 314, the server 102 receives from the Internet the second photograph with a geotag, and which was made within a radius of 450 meters from the first object - the building 202 of the Bolshoi Theater. [143] In alternative implementations of the present technology, the server 102 can receive from the Internet the second photograph with a geotag, which was made within a radius of 450 meters radius of the first photograph.

[144] The second photograph can additionally have one or more description parameters, but this is not be necessary for the second photograph.

[145] The second photograph can, for example, be a photograph taken, like the first photograph, at the point 208 and having a geotag of 55°45'35" N 37°37'10" E. Such a photograph could, potentially, not be identified as the first photograph because either it does not have any description parameters that allow to identify it with the first object or the description parameters were not sufficient for identification. For example, the text "Beautiful day" under the photograph does not exclude the fact that it shows the facade of the building 202, yet, this photograph could not have bene selected as the first photograph as the first proximity coefficient has not exceeded a predefined threshold value of proximity.

[146] For example, one type of search may be a search for photographs with geotags located within the Teatralnaya Square 206, which offers a view of the building 202 of the Bolshoi Theater. As such, the second photograph can be found, which had not been received at the step 306 as the first photograph (in alternative implementations of the present technology - as one of the first photographs).

[147] Next, the method 300 then proceeds to step 316.

[148] Step 316 - based on a comparison of the second photograph with the first photograph using descriptors of the characteristic features of an image, determining an indicator of similarity between the second photograph and the first photograph

[149] At step 316, the server 102 effects, based on a comparison of the second photograph with the first photograph using descriptors of the characteristic features of an image, determining the indicator of similarity between the first photograph showing the first object - the building 202 of the Bolshoi Theater, with the second photograph.

[150] As a person skilled in the art would understand from the above description, the second photograph may have location parameters similar to the location parameters of the first photograph (i.e., both photographs can be taken from the same point 208 or from points near each other (e.g., within the Teatralnaya Square 206)).

[151] In the given implementation of the present technology, in order to effect the identification, at step 316, the server 102 can determine the indicator of similarity between the first and second photographs based on SURF descriptors (Speeded Up Robust Features). Such an analysis consists of marking some of the key points and small areas surrounding them on the two photographs, and the subsequent comparison of these points. A key point is a point that has some features that significantly distinguish it from the main mass of points. For example, this can be line edges, small circles, sudden changes in lighting, angles, etc. Small areas surrounding points are chosen because a small area of a photograph will mostly not be subject to distortions in perspective and scale, but if the areas are too small, they will not be suitable as they will not hold enough information. The SURF method searches for specific points using the Hessian matrix, the determinant of which reaches the extremum of the points of maximum change of the gradient of brightness and detects well spots, corners and edges of lines. This method is invariant to scale, rotation of the photograph, noise, overlap by other objects, change in brightness and contrast, and thereby provides for the possibility of determining that both photographs show the same object, even if the two photographs are of different scale, and/or were not taken from the same angle, and/or have distortions due to panoramic shooting.

[152] In alternative implementations of the present technology, the server 102 can determine the indicator of similarity between the first photograph and the second photograph based on any other suitable descriptors.

[153] The method 300 then proceeds to step 318.

[154] Step 318 - in response to exceeding the indicator of similarity between the second photograph and the first photograph, associating the second photograph with the first point of interest

[155] At step 318, in response to exceeding the indicator of similarity between the second photograph and the first photograph, the server 102 associates the second photograph with the first point of interest. This associating is possible due to the fact that at step 312, the server 102 has associated the first photograph with the first point of interest. Given that at step 318, the server 102 has determined that the second photograph is visually similar to the first photograph, this allows the second photograph to be considered as showing the same first object as in the first photograph.

[156] Next, the method 300 proceeds to step 320.

[157] Step 320 - calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating the importance coefficient of the second point of interest based on the quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph

[158] As a person skilled in the art would understand, steps 306 - 318 can be applied to a plurality of photographs. Thus, for example, at steps 306 - 312 there can be a plurality of first photographs with description parameters and the location parameters allowing to associate them with the first point of interest. For example, up to 30,000 photographs of an object that is an attraction in the center of Moscow can be found, and these photographs have a suitable geotag and a correct description allowing to confirm that the given photographs indeed show the given attraction.

[159] Next, at steps 314 - 316, the server 102 can find within a certain radius of the corresponding object (or within a certain radius of the area where the first photographs were taken) a plurality of second photographs that can potentially be similar to the first photographs from the plurality of first photographs.

[160] Next, at step 318, the server 102 may compare the second photographs from the plurality of second photographs with one or more of the first photographs. As a result of this comparison, the server 102 may determine that some photographs from the plurality of second photographs are significantly similar to some of the first photographs that were used for the comparison. As a result, the server 102 will determine the plurality of the photographs showing the first object. The implementation of this second step of determining the popularity allows to find additional photographs of the object, which could not have been found if only using the first step of determining the popularity. [161] The method 300 is also suitable to determine the popularity of the second object. On the Internet, there are photographs showing another object, namely the monument 204 of A. M. Ostrovsky, and, there will be text in the name of the file or in the photograph caption on a website or in a hyperlink to a photograph, etc., which, when processed, will lead to the second proximity coefficient being higher than the first proximity coefficient. The first photograph (or plurality of first photographs) will be associated with the second object. Then, as a result of the implementation of the second search, the second photograph (or the plurality of second photographs) will be received, which will be compared with one (or several) first photograph(s), and some of the second photographs from the plurality of second photographs will be considered substantially similar to the first photograph that was used for the comparison. These second photographs will also be associated with the second point of interest.

[162] As a result, the first point of interest will be associated with a certain first quantity of photographs and the second point of interest will be associated with a certain second quantity of photographs.

[163] Since the server 102 will have information about the first quantity of photographs associated with the first point of interest and about the second quantity of photographs associated with the second point of interest, the server 102 can calculate the importance coefficient of the first point of interest based on the quantity of photographs in the plurality of photographs associated with the first point of interest, and the importance coefficient of the second point of interest based on the quantity of photographs in the plurality of photographs associated with the second point of interest.

[164] In some implementations of the present technology, in which at least one description parameter of any of the first photograph and the second photograph is a photographer identifier, when calculating the importance coefficient of the first point of interest based on the quantity of photographs in the plurality of photographs associated with the first point of interest and/or the importance coefficient of the second point of interest based on the quantity of photographs in the plurality of photographs associated with the second point of interest, at least one reduction coefficient is used when in the first plurality of photographs associated with the corresponding point of interest, the quantity of photographs with the same photographer identifier exceeds a predefined value. [165] Thus, as an illustrative example, the server 102 receives from the Internet the plurality of photographs, and the server 102 associates 56 photographs with the first point of interest, and 64 photos with the second point of interest. The server 102 also identifies, using the photographer identifiers contained in the received photographs, that all 56 photographs that the server 102 has associated with the first point of interest were taken by different photographers. The server 102 also identifies, using the photographer identifiers contained in the received photos, that of the 64 photographs that the server 102 has associated with the second point of interest, 40 photographs were taken by the same photographer. The fact that a significant number of photographs of the same object were taken by the same photographer can indicate that this particular photographer has certain personal preferences. In connection with this, the server 102 can apply reduction factors to the calculation of the importance coefficient of the point of interest in respect of which numerous photographs taken by the same photographer have been found. For example, the first 10 photographs of the same object taken by the same photographer can be taken into account when calculating the importance coefficient of the corresponding point of interest with a coefficient of 1; the following 10 photographs can be taken into account with a coefficient of 0.75; the next 10 photographs can be taken into account with a coefficient of 0.6, etc. The use of such coefficients can mitigate the inaccuracies in the calculation of the importance coefficient of the point of interest caused by the subjective preferences of one or more individual photographers.

[166] Next, the method 300 proceeds to step 322.

[167] Step 322 - in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning to the first point of interest a rating higher than the rating of the second point of interest

[168] At step 322, the server 102, in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigns to the first point of interest a rating higher than the rating of the second point of interest. This higher rating of the first point of interest, with which the greatest number of photographs is associated, can be used by server 102 to rank search results that the server 102 can show in response to a request of the user 111 to provide him a list of nearby attractions. For example, when there is such a large quantity of attractions in a particular area that it is difficult to present them on the display 118 of the electronic device 112, the server 102 can hide objects with a relatively low rating when generating a SERP.

[169] Within the present description, it should be understood that in each instance the receiving of data from any electronic device, and/or from any email server, and/or from any other server is indicated, the receiving of an electronic or any other signal from a suitable electronic device (server, email server) can be used, and the displaying on the device screen can be implemented as the transmission of the signal to the display, comprising certain information which can further be interpreted in a certain way and at least partially displayed on the screen of the electronic device. The transmission and reception are not always mentioned everywhere within the present description to simplify the description and for a better understanding of the present solution. Signals can be transmitted by optical methods (e.g., via fiber-optic connection), by electronic methods (via wired or wireless connection), by mechanical methods (transmission of the pressure, temperature and/or other physical parameters by means of which the transmission of the signal is possible).

CLAUSES

[170] In accordance with the above description, the present technology can be summarized as follows.

[171] Clause 1 : A method of ranking at least two points of interest from a plurality of points of interest using photograph rating, the method executable at a server (102), a first point of interest representing a first object (202), a second point of interest representing a second object (204), the second point of interest being associated with a second plurality of photographs showing the second object (204), and each point of interest from the plurality of points of interest being associated with a predefined plurality of parameters of the corresponding point of interest, the method comprising: receiving (304) a first plurality of parameters of the first point of interest, the first plurality of parameters of the first point of interest, including at least one location parameter and at least one description parameter describing the first object (202) represented by the first point of interest; executing a first step (306-312) of determining a popularity of the first object (202) represented by the first point of interest, including: receiving (306) a first photograph associated with a first plurality of parameters of the first photograph, the first plurality of parameters of the first photograph including at least one location parameter and at least one description parameter; calculating (308) a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest; in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating (312) the first photograph with the first point of interest; executing a second step (314-318) of the determining of the popularity of the first object (202) represented by the first point of interest, including: receiving (314) a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters of the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest; based on a comparison of the second photograph with the first photograph by using descriptors of characteristic features of an image, determining (316) an indicator of similarity between the second photograph and the first photograph; in response to exceeding the indicator of similarity between the second photograph and the first photograph, associating (318) the second photograph with the first point of interest; calculating (320) an importance coefficient of the first point of interest based on a quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating an importance coefficient of the second point of interest based on a quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph; in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning (322) to the first point of interest a rating higher than to the second point of interest.

[172] Clause 2: The method of clause 1, further comprising generating a plurality of points of interest, such that each point of interest from the plurality of points of interest corresponds to a corresponding single object.

[173] Clause 3: The method of clause 2, wherein the generating the plurality of points of interest includes receiving by the server (102) of information associated with objects that can potentially be represented by points of interest, including receiving a predefined plurality of parameters of each object from a plurality of objects, and the predefined plurality of parameters includes at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding points of interest.

[174] Clause 4: The method of clause 3, wherein the receiving by the server (102) of information associated with objects that can potentially be represented by points of interest is effected using public data sources.

[175] Clause 5: The method of any of clauses 1-4, wherein at least one of the receiving the first photograph and the receiving the second photograph is effected using public data sources.

[176] Clause 6: The method of any of clauses 1-5, wherein the second plurality of parameters of the second photograph includes at least one of:

(1) a location parameter, and (2) the at least one description parameter.

[177] Clause 7: The method of any of clauses 1-6, wherein the determining of the indicator of similarity between the second photograph and the first photograph comprises comparing the plurality of parameters of the second photograph and the plurality of parameters of the first photograph.

[178] Clause 8: The method of any of clauses 1-7, wherein the at least one description parameter of the first object (202) is at least one of a name of an object and a description of an object.

[179] Clause 9: The method of any of clauses 1-8, wherein the calculating the first proximity coefficient is executed using the at least one location parameter of the first photograph and the at least one location parameter of the first point of interest.

[180] Clause 10: The method of any of clauses 1-9, wherein the calculating of the first proximity coefficient is executed using the at least one description parameter of the first photograph and the at least one description parameter of the first point of interest.

[181] Clause 11 : The method of any of clauses 1-10, wherein at least one description parameter of at least one of the first photograph and the second photograph is a photographer identifier , and while calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, at least one reduction coefficient is used if the quantity of photographs with the same photographer identifier in the first plurality of the photographs associated with the first point of interest exceeds a predefined value.

[182] Clause 12: The method of any of clauses 1-11, wherein the first photograph is a third plurality of first photographs, the second photograph is a fourth plurality of second photographs, and the determining of the indicator of similarity between the second photograph and the first photograph is effected by comparing each photograph from the fourth plurality of second photographs with at least some of the photographs from the third plurality of first photographs.

[183] Clause 13: The method of any of clauses 1-12, further comprising receiving a user (111) request to provide information associated with any of the first object (202) and the second object (204), and in response to the receiving of the user (111) request to provide information, generating by the server (102) search results based on a rating of the first point of interest and a rating of the second point of interest.

[184] Clause 14: The method of clause 13, further comprising sending the search results by the server (102) to a user (111) electronic device (112) to be displayed to the user (111).

[185] Clause 15: A server (102) including a processor, the processor being configured to render the server (102) to effect the method of any of clauses 1-14.

Claims

1. A method of ranking at least two points of interest from a plurality of points of interest using photograph rating, the method executable at a server, a first point of interest representing a first object, a second point of interest representing a second object, the second point of interest being associated with a second plurality of photographs showing the second object, and each point of interest from the plurality of points of interest being associated with a predefined plurality of parameters of the corresponding point of interest, the method comprising: receiving a first plurality of parameters of the first point of interest, the first plurality of parameters of the first point of interest, including at least one location parameter and at least one description parameter describing the first object represented by the first point of interest; executing a first step of determining a popularity of the first object represented by the first point of interest, including: receiving a first photograph associated with a first plurality of parameters of the first photograph, the first plurality of parameters of the first photograph including at least one location parameter and at least one description parameter; calculating a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest; in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating the first photograph with the first point of interest; executing a second step of the determining of the popularity of the first object represented by the first point of interest, including: receiving a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters of the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest; based on a comparison of the second photograph with the first photograph by using descriptors of characteristic features of an image, determining an indicator of similarity between the second photograph and the first photograph; in response to exceeding the indicator of similarity between the second photograph and the first photograph, associating the second photograph with the first point of interest; calculating an importance coefficient of the first point of interest based on a quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating an importance coefficient of the second point of interest based on a quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph; in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning to the first point of interest a rating higher than to the second point of interest.

2. The method of claim 1, further comprising generating a plurality of points of interest, such that each point of interest from the plurality of points of interest corresponds to a corresponding single object.

3. The method of claim 2, wherein the generating the plurality of points of interest includes receiving by the server information associated with objects that can potentially be represented by points of interest, including receiving a predefined plurality of parameters of each object from a plurality of objects, and the predefined plurality of parameters includes at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding points of interest.

4. The method of claim 3, wherein the receiving by the server of information associated with objects that can potentially be represented by points of interest is effected using public data sources.

5. The method of claim 1, wherein at least one of the receiving the first photograph and the receiving the second photograph is effected using public data sources.

6. The method of claim 1, wherein the second plurality of parameters of the second photograph includes at least one of:

(1) a location parameter, and

(2) at least one description parameter.

7. The method of claim 1 , wherein the determining of the indicator of similarity between the second photograph and the first photograph comprises comparing the plurality of parameters of the second photograph and the plurality of parameters of the first photograph.

8. The method of claim 1, wherein the at least one description parameter of the first object is at least one of a name of an object and a description of an object.

9. The method of claim 1 , wherein the calculating the first proximity coefficient is executed using the at least one location parameter of the first photograph and the at least one location parameter of the first point of interest.

10. The method of claim 1, wherein the calculating of the first proximity coefficient is executed using the at least one description parameter of the first photograph and the at least one description parameter of the first point of interest.

11. The method of claim 1, wherein at least one description parameter of at least one of the first photograph and the second photograph is a photographer identifier , and while calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, at least one reduction coefficient is used if the quantity of photographs with the same photographer identifier in the first plurality of the photographs associated with the first point of interest exceeds a predefined value.

12. The method of claim 1, wherein the first photograph is a third plurality of first photographs, the second photograph is a fourth plurality of second photographs, and the determining of the indicator of similarity between the second photograph and the first photograph is effected by comparing each photograph from the fourth plurality of second photographs with at least some of the photographs from the third plurality of first photographs.

13. The method of claim 1, further comprising receiving a user request to provide information associated with any of the first object and the second object, and in response to the receiving of the user request to provide information, generating by the server search results based on a rating of the first point of interest and a rating of the second point of interest.

14. The method of claim 13, further comprising sending the search results by the server to a user electronic device to be displayed to the user.

15. A server including a processor, the processor being configured to render the server to execute: receiving a first plurality of parameters of a first point of interest, the first plurality of parameters of the first point of interest including at least one location parameter and at least one description parameter describing a first object represented by the first point of interest; executing a first step of determining a popularity of the first object represented by the first point of interest, including: receiving a first photograph associated with a first plurality of parameters of the first photograph, the first plurality of parameters of the first photograph including at least one location parameter and at least one description parameter; calculating a first proximity coefficient using at least one parameter from the first plurality of parameters of the first photograph and at least one parameter from the first plurality of parameters of the first point of interest; in response to the first proximity coefficient exceeding a predefined threshold value of proximity, associating the first photograph with the first point of interest; executing a second step of the determining the popularity of the first object represented by the first point of interest, including: receiving a second photograph associated with a second plurality of parameters of the second photograph, and at least some parameters of the second plurality of parameters of the second photograph differ, at least in part, from corresponding parameters of the first plurality of parameters of the first photograph, and there being no confirmed connection between the second photograph and the first point of interest; based on a comparison of the second photograph with the first photograph using descriptors of characteristic features of an image, determining an indicator of similarity between the second photograph and the first photograph; in response to exceeding of indicator of similarity between the second photograph and the first photograph, associating the second photograph with the first point of interest; calculating an importance coefficient of the first point of interest based on a quantity of photographs in the first plurality of photographs associated with the first point of interest, and calculating the importance coefficient of the second point of interest based on a quantity of photographs in the second plurality of photographs associated with the second point of interest, and the first plurality of photographs associated with the first point of interest includes the first photograph and the second photograph; in response to the importance coefficient of the first point of interest exceeding the importance coefficient of the second point of interest, assigning to the first point of interest a rating higher than a rating of the second point of interest.

16. The server of claim 15, wherein the processor is further configured to render the server to generate a plurality of points of interest, such that each point of interest from the plurality of points of interest corresponds to a corresponding single object.

17. The server of claim 16, wherein the generating the plurality of points of interest includes receiving by the server of information associated with objects that can potentially be represented by points of interest, including receiving a predefined plurality of parameters of each object from a plurality of objects, and the predefined plurality of parameters includes at least one location parameter and at least one description parameter, and assigning the corresponding parameters to the corresponding points of interest.

18. The server of claim 17, wherein the receiving by the server of information associated with objects that can potentially be represented by points of interest is effected using public data sources.

19. The server of claim 15, wherein at least one of the first photograph and the second photograph is effected using public data sources.

20. The server of claim 15, wherein the second plurality of parameters of the second photograph includes at least one of:

(1) a location parameter, and

(2) at least one description parameter.

The server of claim 15, wherein the determining of the indicator of similarity between the second photograph and the first photograph comprises comparing the plurality of parameters of the second photograph and the plurality of parameters of the first photograph.

22. The server of claim 15, wherein the at least one description parameter of the first object is at least one of a name of an object and a description of an object.

23. The server of claim 15, wherein the calculating the first proximity coefficient is executed using the at least one location parameter of the first photograph and the at least one location parameter of the first point of interest.

24. The server of claim 15, wherein the calculating of the first proximity coefficient is executed using the at least one description parameter of the first photograph and at the least one description parameter of the first point of interest.

25. The server of claim 15, wherein at least one description parameter of at least one of the first photograph and the second photograph is a photographer identifier, and while calculating the importance coefficient of the first point of interest based on the quantity of photographs in the first plurality of photographs associated with the first point of interest, at least one reduction coefficient is used if the quantity of the photographs with the same photographer identifier in the first plurality of the photographs associated with the first point of interest exceeds a predefined value.

26. The server of claim 15, wherein the first photograph is a third plurality of the first photographs, the second photograph is a fourth plurality of second photographs, and the determining of the indicator of similarity between the second photograph and the first photograph is effected by comparing each photograph from the fourth plurality of the second photographs with at least some of the photographs from the third plurality of first photographs.

27. The server of claim 15, wherein the processor is further configured to render the server to receive a user request to provide information associated with any of the first object and the second object, and, in response to receiving the user request to provide information, generate search results based on the rating of the first point of interest and the rating of the second point of interest.

28. The server of claim 27, wherein processor is further configured to render server to send the search results to a user electronic device to be displayed to the user.