CN113704378B - A method, device, equipment and storage medium for determining accompanying information - Google Patents
A method, device, equipment and storage medium for determining accompanying information Download PDFInfo
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- CN113704378B CN113704378B CN202111029928.9A CN202111029928A CN113704378B CN 113704378 B CN113704378 B CN 113704378B CN 202111029928 A CN202111029928 A CN 202111029928A CN 113704378 B CN113704378 B CN 113704378B
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2474—Sequence data queries, e.g. querying versioned data
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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Abstract
本发明实施例公开了一种伴随信息的确定方法，包括：确定被伴随的目标对象，根据目标对象的唯一信息查询目标对象在设定时间范围内每个轨迹点的轨迹数据；根据轨迹数据将轨迹点划分为设定个数的伴随区域，并查询在设定时间范围内，与目标对象在至少两个伴随区域中共同出现的伴随对象；获取各伴随对象的伴随轨迹数据，并根据伴随轨迹数据确定各伴随对象对应的伴随率，将伴随轨迹数据和伴随率确定为伴随信息。本发明实施例提供的伴随信息的确定方法，通过根据目标对象的轨迹数据划分伴随区域，进而确定与目标对象共同出现的伴随对象及对应的伴随信息，实现了利用大数据对时间和空间上的分布规律进行分析和挖掘，提高了轨迹伴随率及方法的可靠性。
The embodiment of the present invention discloses a method for determining accompanying information, including: determining the target object to be accompanied, querying the trajectory data of each trajectory point of the target object within a set time range according to the unique information of the target object; dividing the trajectory point into a set number of accompanying areas according to the trajectory data, and querying the accompanying objects that co-appear with the target object in at least two accompanying areas within the set time range; obtaining the accompanying trajectory data of each accompanying object, and determining the accompanying rate corresponding to each accompanying object according to the accompanying trajectory data, and determining the accompanying trajectory data and the accompanying rate as the accompanying information. The method for determining accompanying information provided by the embodiment of the present invention divides the accompanying area according to the trajectory data of the target object, and then determines the accompanying object and the corresponding accompanying information that co-appears with the target object, thereby realizing the use of big data to analyze and mine the distribution rules in time and space, and improving the reliability of the trajectory accompanying rate and the method.
Description
Technical Field
The present invention relates to the field of information technologies, and in particular, to a method, an apparatus, a device, and a storage medium for determining accompanying information.
Background
The accompanying pattern of spatiotemporal trajectories refers to a group of moving objects (moving objects) moving together within a defined range for at least a length of w, such a motion pattern being called an accompanying pattern. In recent years, big data becomes a new innovative, competitive and productive frontier field, and based on the acquisition, processing, knowledge management and utilization of the whole big data, opportunities and challenges are provided for solving the track analysis problem in the accompanying mode.
With rapid propagation of network information and increasingly complex changing environments, hidden association, rules and development trends in track points of a plurality of mobile objects in an accompanying mode are difficult to find by traditional methods and technical means such as query, statistics and the like in the past, and the track information of the mobile objects and accompanying objects of the same row are restricted to be determined to a certain extent due to low data quality and unstable data. In addition, the track of other peer objects is found to have the problem of low accompanying rate by moving the object track point data, so that the result is deviated from the actual situation.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for determining accompanying information, which realize accurate determination of track information of an accompanying object of a target object.
In a first aspect, an embodiment of the present invention provides a method for determining accompanying information, including:
determining an accompanied target object, and inquiring track data of each track point of the target object within a set time range according to unique information of the target object;
Dividing the track points into a set number of accompanying areas according to the track data, and inquiring the accompanying objects which co-occur with the target object in at least two accompanying areas within the set time range;
And acquiring the accompanying track data of each accompanying object, determining the accompanying rate corresponding to each accompanying object according to the accompanying track data, and determining the accompanying track data and the accompanying rate as the accompanying information.
Further, dividing the track point into a set number of accompanying areas according to the track data, including:
determining the track radius of the track point, and expanding the track point into a track area;
Dividing the track areas according to the set number, and determining the accompanying areas of the set number;
and determining the accompanying area where each track point is located according to the track data.
Further, determining a track radius of the track point, expanding the track point into a track area, and including:
expanding each track point into a circular area according to the track radius;
Supplementing a circular region set of each track point, and determining a rectangular region containing the circular region set as the track region.
Further, querying a companion object co-occurring with the target object in at least two companion areas within the set time range, including:
Taking the accompanying areas as query conditions, and acquiring objects which coexist with the target object in the set time range in each accompanying area;
An object co-occurring with the target object in at least two companion regions is determined as the companion object.
Further, determining the corresponding concomitance rate of each concomitance object according to the concomitance track data comprises:
For each companion object, determining a target companion area coexisting with the target object according to the corresponding companion track data;
And acquiring a preset intermediate value of each target accompanying region and a threshold value of each accompanying region, and taking a quotient of the sum of each intermediate value and the sum of each threshold value as an accompanying rate corresponding to the accompanying object.
Further, obtaining a preset intermediate value of each target accompanying area includes:
For each companion object, determining a companion time at which the companion object and the target object co-occur according to the corresponding companion track data;
And if the accompanying time exceeds a set time threshold, taking the sum of the intermediate value of the target accompanying area corresponding to the accompanying object and a preset added value as a new intermediate value.
Further, after determining the accompanying track data and the accompanying rate as the accompanying information, the method further includes:
and arranging the accompanying information in a reverse order according to the magnitude of the accompanying rate.
In a second aspect, an embodiment of the present invention further provides a device for determining accompanying information, including:
The track data query module is used for determining an accompanied target object, and querying track data of each track point of the target object within a set time range according to unique information of the target object;
The companion object inquiry module is used for dividing the track points into a set number of companion areas according to the track data and inquiring companion objects which co-occur with the target object in at least two companion areas within the set time range;
And the accompanying information determining module is used for acquiring the accompanying track data of each accompanying object, determining the accompanying rate corresponding to each accompanying object according to the accompanying track data and determining the accompanying track data and the accompanying rate as the accompanying information.
Optionally, the companion object query module is further configured to:
determining the track radius of the track point, and expanding the track point into a track area;
Dividing the track areas according to the set number, and determining the accompanying areas of the set number;
and determining the accompanying area where each track point is located according to the track data.
Optionally, the companion object query module is further configured to:
expanding each track point into a circular area according to the track radius;
Supplementing a circular region set of each track point, and determining a rectangular region containing the circular region set as the track region.
Optionally, the companion object query module is further configured to:
Taking the accompanying areas as query conditions, and acquiring objects which coexist with the target object in the set time range in each accompanying area;
An object co-occurring with the target object in at least two companion regions is determined as the companion object.
Optionally, the accompanying information determining module is further configured to:
For each companion object, determining a target companion area coexisting with the target object according to the corresponding companion track data;
And acquiring a preset intermediate value of each target accompanying region and a threshold value of each accompanying region, and taking a quotient of the sum of each intermediate value and the sum of each threshold value as an accompanying rate corresponding to the accompanying object.
Optionally, the accompanying information determining module is further configured to:
For each companion object, determining a companion time at which the companion object and the target object co-occur according to the corresponding companion track data;
And if the accompanying time exceeds a set time threshold, taking the sum of the intermediate value of the target accompanying area corresponding to the accompanying object and a preset added value as a new intermediate value.
Optionally, the device further includes an arrangement module, configured to arrange the accompanying information in a reverse order according to the magnitude of the accompanying rate.
In a third aspect, an embodiment of the present invention further provides a computer device for determining accompanying information, including:
Comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which processor implements the method of determining accompanying information according to any of the embodiments of the invention when the program is executed.
In a fourth aspect, an embodiment of the present invention further provides a storage medium having stored thereon a computer program, which when executed by a processing device, implements a method for determining accompanying information according to any of the embodiments of the present invention.
The method comprises the steps of firstly determining an accompanying target object, inquiring track data of each track point of the target object within a set time range according to unique information of the target object, dividing the track points into a set number of accompanying areas according to the track data, inquiring accompanying objects which appear in the set time range together with the target object in at least two accompanying areas, finally obtaining accompanying track data of each accompanying object, determining accompanying rate corresponding to each accompanying object according to the accompanying track data, and determining the accompanying track data and the accompanying rate as accompanying information. According to the method for determining the accompanying information, the accompanying area is divided according to the track data of the target object, so that the accompanying object and the corresponding accompanying information which appear together with the target object are determined, the distribution rule and the change trend in time and space are analyzed and mined by utilizing big data, the track accompanying rate and the reliability of the method are improved, data support is provided for formulating a control strategy, identifying a rule mode, optimizing resource deployment, area planning and the like, and the scheduling capacity and the same-line decision level of related departments are improved.
Drawings
FIG. 1 is a flowchart of a method for determining accompanying information in accordance with a first embodiment of the present invention;
FIG. 2 is a flow chart of a method for partitioning a companion area according to a second embodiment of the present invention;
FIG. 3 is a flowchart of a method for determining a companion rate in a third embodiment of the present invention;
FIG. 4 is a schematic diagram of a device for determining accompanying information according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device in a fifth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a method for determining accompanying information provided in an embodiment of the present invention, where the method may be performed by an apparatus for determining accompanying information, where the apparatus may be composed of hardware and/or software, and may be generally integrated into a device having an accompanying information determining function, where the device may be an electronic device such as a server or a server cluster. As shown in fig. 1, the method specifically comprises the following steps:
Step 110, determining the accompanied target object, and inquiring the track data of each track point of the target object within a set time range according to the unique information of the target object.
The accompanying target object may be a person carrying a device having a positioning function such as a mobile phone or a vehicle equipped with a positioning device such as a GPS, etc., and the unique information of the target object may be information related to the target object and used for distinguishing the target object from other objects, for example, if the target object is a person, the unique information may be a mobile phone number or an identification card number, etc., and if the target object is a vehicle, the unique information may be a license plate number, etc. The set time range may be a time length for tracking a track of the target object set manually, where the track is composed of a plurality of track points, for example, if the set time range is 1 hour, the position information of the target object is acquired every 5 minutes, 13 track points of the target object may be acquired, each track point has corresponding track data, and the track data may include information such as an object number, longitude and latitude, and current time.
In this embodiment, the method for querying the track data of each track point of the target object within the set time range according to the unique information of the target object may include using the unique information and the time range of the target object as query conditions, for example, a mobile phone number of the target object and a time period to be queried may be input, querying in a track database, and obtaining the distribution of each track point of the target object on the map within the specified time range, and the information such as the object number, longitude and latitude, and current time corresponding to each track point.
Step 120, dividing the track points into a set number of accompanying areas according to the track data, and inquiring the accompanying objects which are co-present with the target object in at least two accompanying areas within a set time range.
The companion region may be a plurality of spatio-temporal small regions that can be processed by the existing resources of the system, and the companion object may be an object that co-appears with the target object in at least two companion regions. For example, if the target object Zhang Sanhe appears in the four accompanying areas A, B, C, D within a set time range, and if Lifour and Zhang Sanhe appear in the A, B area together within the same time range, lifour may be regarded as the accompanying object Zhang Sanhe.
In this embodiment, after determining the track points and track data of the target object, each point may be expanded to form a region having a certain area, and then the formed region is divided into a set number of small regions, where each small region is an accompanying region. Further, the companion region in which the target object appears may be determined, and then a query is made in the track database to find objects that co-appear with the target object in at least two companion regions within a set time frame, and these objects are determined as companion objects of the target object.
Alternatively, the method of querying the companion object co-occurring with the target object in the at least two companion areas within the set time range may be performed by acquiring, as the query condition, the object co-occurring with the target object within the set time range in each companion area, and determining the object co-occurring with the target object in the at least two companion areas as the companion object.
Specifically, after the concomitant regions are divided, the concomitant region in which the target object appears in the set time range may be determined, then, the objects that appear simultaneously with the target object in each concomitant region in which the target object appears are sequentially queried, and finally, the concomitant objects that appear simultaneously with the target object in at least two concomitant regions are determined. For example, in the set time range, if the target object Zhang three appears in the four accompanying areas A, B, C, D, and the accompanying area a is used as the query condition in the track database, it is possible to find out that the accompanying areas a and Wang Wujun appear in the accompanying area a together with Zhang three, then continue to query the accompanying area B, find out that the accompanying areas C and D appear in the accompanying area together with Zhang three, and continue to query the accompanying areas C and D, respectively find out that Zhao Liu and Liu Qi appear in the accompanying area together with the target object, and in all the objects which appear in the accompanying area together with Zhang three, only the number of the accompanying areas which appear in the accompanying area together with Zhang three reaches two, so that the accompanying object of Zhang three is the like.
Step 130, acquiring the accompanying track data of each accompanying object, determining the accompanying rate corresponding to each accompanying object according to the accompanying track data, and determining the accompanying track data and the accompanying rate as accompanying information.
The accompanying trajectory data may include an accompanying object number, the number and number of accompanying areas in which the accompanying object and the target object coexist, the time of the coexistence, the longitude and latitude, and the like, and the accompanying rate may be a value calculated from the accompanying trajectory and capable of characterizing the reliability of the accompanying object.
It will be appreciated that there may be one or more companion objects of the target object, and after each companion object is determined, companion trajectory data of each companion object may be obtained, that is, when, where, in which companion regions each companion object co-appears with the target object may be determined, and a companion rate corresponding to each companion object may be calculated, where the companion rate may reflect the degree of association of the companion object with the target object and the reliability of the companion object to some extent.
In the present embodiment, after the accompanying track data and the accompanying rate are determined as the accompanying information, the accompanying information may be arranged in reverse order according to the magnitude of the accompanying rate.
Alternatively, the value of the concomitance rate may be between 0 and 100%, and after calculating the concomitance rate of each concomitance object, the concomitance information corresponding to each concomitance object may be arranged according to the concomitance rate, preferably, the concomitance information may be arranged in a reverse order according to the magnitude of the concomitance rate, so as to determine the object associated most closely with the target object.
The method comprises the steps of firstly determining an accompanying target object, inquiring track data of each track point of the target object within a set time range according to unique information of the target object, dividing the track points into a set number of accompanying areas according to the track data, inquiring accompanying objects which appear in the set time range together with the target object in at least two accompanying areas, finally obtaining accompanying track data of each accompanying object, determining accompanying rate corresponding to each accompanying object according to the accompanying track data, and determining the accompanying track data and the accompanying rate as accompanying information. According to the method for determining the accompanying information, the accompanying area is divided according to the track data of the target object, so that the accompanying object and the corresponding accompanying information which appear together with the target object are determined, the distribution rule and the change trend in time and space are analyzed and mined by utilizing big data, the track accompanying rate and the reliability of the method are improved, data support is provided for formulating a control strategy, identifying a rule mode, optimizing resource deployment, area planning and the like, and the scheduling capacity and the same-line decision level of related departments are improved.
Example two
Fig. 2 is a flowchart of a method for partitioning an accompanying area according to a second embodiment of the present invention, where the present embodiment is applicable to a case of partitioning an accompanying area, as shown in fig. 2, and specifically includes the following steps:
And 121, determining the track radius of the track point, and expanding the track point into a track area.
The track radius can be the radius of a circular area expanded by taking the track point as the center of a circle, and the track area can be the area of the track point after being subjected to expansion, supplementation and other treatments.
In this embodiment, each track point may be expanded into a circle according to the track radius, and all circles are grouped together and supplemented to be expanded into a rectangular track area.
Optionally, the track radius of the track points is determined, the track points are expanded into track areas in a mode that each track point is expanded into a circular area according to the track radius, the circular area set of each track point is supplemented, and a rectangular area containing the circular area set is determined as the track area.
Specifically, each track point can be converted into a geographic hash (Geohash) value through a setting algorithm according to track data and a set track radius, the Geohash value can be regarded as a character string, the more the number of bits of the same character string is, the closer the representing distance is, and the longer the character string is, the more accurate the representing range is. In practical application, under the condition that equipment and facilities are relatively dense and the data quality is better, the Geohash value bit number can be set higher, so that the method has the advantages that the data is relatively accurate, the focusing on the data and the service can be performed, and if the equipment and facilities are relatively rare or the data quality continuity is not high, the Geohash value bit number can be properly adjusted down, the coverage of a passing range is increased, and the situation of missing or insufficient coverage of the data can be supplemented.
Further, after the track points are converted into the Geohash values, the circular area expanded by taking each track point as the center of a circle is determined due to the fact that the track radius information is contained in the track points, and meanwhile the problem of the boundary of the Geohash values is considered, namely, points which are easy to ignore exist between the circular areas, so that a cutting and complementing method can be adopted to supplement the peripheral areas of the circles to form a circular circumscribed rectangle, and the circumscribed rectangle is determined to be the track area.
Step 122, dividing the track areas by the set number, and determining the set number of accompanying areas.
In this embodiment, after determining all the track areas, the track areas may be divided, and the number of divisions may be preset, for example, 9 or more, and each divided area is an accompanying area.
Step 123, determining the accompanying area where each track point is located according to the track data.
As described above, the track points may be converted into the Geohash values, and the more the same number of bits indicates the closer the distance, whether the track points are located in the same accompanying region may be determined according to the number of the same number of bits, for example, the track points corresponding to the Geohash values with the same first 5 bits of characters may be made to belong to the same accompanying region.
The embodiment of the invention firstly determines the track radius of the track points, expands the track points into track areas, then divides the track areas according to the set number, determines the set number of accompanying areas, and finally determines the accompanying areas where each track point is located according to the track data. According to the method for dividing the accompanying areas, provided by the embodiment of the invention, the trace points are expanded and supplemented, and the accompanying areas are further divided according to the set number, so that the determination of the accompanying objects is more accurate and reliable, and omission is not easy to occur.
Example III
Fig. 3 is a flowchart of a method for determining a companion rate according to a third embodiment of the present invention, where the present embodiment is applicable to a case of determining a companion rate of a companion object, as shown in fig. 3, and specifically includes the following steps:
Step 131, for each companion object, determining a target companion region co-occurring with the target object according to the corresponding companion trajectory data.
In this embodiment, if the accompanying track data corresponding to each accompanying object includes the number and the number of accompanying areas in which the accompanying object and the target object appear together, the target accompanying area corresponding to each accompanying object can be determined from the corresponding accompanying track data.
Step 132, obtaining a preset intermediate value of each target accompanying region and a threshold value of each accompanying region, and taking a quotient of the sum of the intermediate values and the sum of the threshold values as an accompanying rate corresponding to an accompanying object.
Wherein each companion region may be preset with an intermediate value and a threshold value, and the intermediate value is < the threshold value.
In this embodiment, after the target companion area of each companion object is determined, the intermediate value corresponding to each target companion area and the threshold values of all companion areas may be acquired, and the sum of the acquired intermediate values and the threshold value may be used as the companion rate of the corresponding companion object. For example, assuming that there are 10 accompanying regions in total, each region has an intermediate value of 9 and a threshold value of 10, there are 5 and 10 accompanying objects for the target accompanying region, respectively, and the accompanying rates thereof are (5×9)/(10×10) =45% and (10×9)/(10×10) =90%, respectively.
Further, for a companion object that accompanies a target object for a long time, the companion rate of the companion object can be increased by adjusting the intermediate value of the corresponding target companion region.
Alternatively, the method of acquiring the intermediate value of each preset target companion region may be that for each companion object, a companion time in which the companion object and the target object coexist is determined based on the corresponding companion trajectory data, and if the companion time exceeds a set time threshold, the sum of the intermediate value of the target companion region corresponding to the companion object and the preset additional value is taken as a new intermediate value.
Specifically, if it can be determined that the accompanying time in which the accompanying object and the target object coexist exceeds the set time threshold for each accompanying object according to the corresponding accompanying trajectory, then an additional value may be added to the intermediate value of the target accompanying region corresponding to the accompanying object, and the accompanying rate may be calculated using the new intermediate value. For example, assuming that there are 10 accompanying regions in total, the median value of each region is 9, the threshold value is 10, and the number of the target accompanying regions is 10 for the accompanying object accompanying the target object for a long time, the additional value may be set to 0.1, and the calculated accompanying rate is (10×9.1)/(10×10) =91%.
According to the embodiment of the invention, a target accompanying region which is commonly appeared with a target object is determined according to corresponding accompanying track data for each accompanying object, then a preset intermediate value of each target accompanying region and a threshold value of each accompanying region are acquired, and a quotient of the sum of each intermediate value and the sum of each threshold value is taken as an accompanying rate corresponding to the accompanying object. According to the method for determining the companion rate, provided by the embodiment of the invention, the companion rate is determined more reasonably by setting the intermediate value and the threshold value of the companion region and setting the additional value of the intermediate value for the target companion region corresponding to the companion object which accompanies for a long time.
Example IV
Fig. 4 is a schematic diagram of a device for determining accompanying information according to a fourth embodiment of the present invention. As shown in FIG. 4, the apparatus includes a trajectory data query module 210, a companion object query module 220, and a companion information determination module 230.
The track data query module 210 is configured to determine an accompanying target object, and query track data of each track point of the target object within a set time range according to unique information of the target object.
The companion object query module 220 is configured to divide the track points into a set number of companion areas according to the track data, and query companion objects that co-occur with the target object in at least two companion areas within a set time range.
Optionally, the companion object query module 220 is further configured to:
The method comprises the steps of determining track radius of track points, expanding the track points into track areas, dividing the track areas according to the set number, determining the set number of accompanying areas, and determining the accompanying areas where the track points are located according to track data.
Optionally, the companion object query module 220 is further configured to:
and supplementing the circular area set of each track point, and determining a rectangular area containing the circular area set as the track area.
Optionally, the companion object query module 220 is further configured to:
Taking the accompanying areas as query conditions, and acquiring objects which appear together with the target object in a set time range in each accompanying area; an object that co-occurs with the target object in at least two companion regions is determined to be a companion object.
The accompanying information determining module 230 is configured to obtain accompanying track data of each accompanying object, determine an accompanying rate corresponding to each accompanying object according to the accompanying track data, and determine the accompanying track data and the accompanying rate as accompanying information.
Optionally, the accompanying information determining module 230 is further configured to:
And acquiring preset intermediate values of the target accompanying areas and threshold values of the accompanying areas, and taking the quotient of the sum of the intermediate values and the sum of the threshold values as the accompanying rate corresponding to the accompanying object.
Optionally, the accompanying information determining module 230 is further configured to:
And if the accompanying time exceeds a set time threshold, taking the sum of the intermediate value of the target accompanying area corresponding to the accompanying object and the preset additional value as a new intermediate value.
Optionally, the device further comprises an arrangement module, which is used for arranging the accompanying information in a reverse order according to the magnitude of the accompanying rate.
The device can execute the method provided by all the embodiments of the disclosure, and has the corresponding functional modules and beneficial effects of executing the method. Technical details not described in detail in this embodiment can be found in the methods provided by all of the foregoing embodiments of the present disclosure.
Example five
Fig. 5 is a schematic structural diagram of a computer device according to a fifth embodiment of the present invention. FIG. 5 illustrates a block diagram of a computer device 312 suitable for use in implementing embodiments of the present invention. The computer device 312 shown in fig. 5 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention. Device 312 is a typical computing device for determining accompanying information.
As shown in FIG. 5, the computer device 312 is in the form of a general purpose computing device. Components of computer device 312 may include, but are not limited to, one or more processors 316, a storage device 328, and a bus 318 connecting the different system components (including storage device 328 and processor 316).
Bus 318 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry standard architecture (Industry Standard Architecture, ISA) bus, micro channel architecture (Micro Channel Architecture, MCA) bus, enhanced ISA bus, video electronics standards association (Video Electronics Standards Association, VESA) local bus, and peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus.
Computer device 312 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 312 and includes both volatile and nonvolatile media, removable and non-removable media.
Storage 328 may include computer system-readable media in the form of volatile memory, such as random access memory (Random Access Memory, RAM) 330 and/or cache memory 332. The computer device 312 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 334 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard disk drive"). Although not shown in fig. 5, a disk drive for reading from and writing to a removable nonvolatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from and writing to a removable nonvolatile optical disk (e.g., a Compact Disc-Read Only Memory (CD-ROM), digital versatile Disc (Digital Video Disc-Read Only Memory), or other optical media), may be provided. In such cases, each drive may be coupled to bus 318 through one or more data medium interfaces. Storage 328 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
Programs 336 having a set (at least one) of program modules 326 may be stored, for example, in storage 328, such program modules 326 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 326 generally perform the functions and/or methods in the described embodiments of the invention.
The computer device 312 may also communicate with one or more external devices 314 (e.g., keyboard, pointing device, camera, display 324, etc.), one or more devices that enable a user to interact with the computer device 312, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 312 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 322. Moreover, the computer device 312 may also communicate with one or more networks such as a local area network (Local Area Network, LAN), a wide area network Wide Area Network, a WAN, and/or a public network such as the internet via the network adapter 320. As shown, network adapter 320 communicates with other modules of computer device 312 via bus 318. It should be appreciated that although not shown, other hardware and/or software modules may be utilized in connection with computer device 312, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, disk array (Redundant Arrays of INDEPENDENT DISKS, RAID) systems, tape drives, and data backup storage systems, among others.
The processor 316 executes various functional applications and data processing by running a program stored in the storage device 328, for example, to implement the method of determining accompanying information provided by the above-described embodiments of the present invention.
Example six
The embodiment of the invention provides a computer readable storage medium, on which a computer program is stored, which when executed by a processing device, implements a method for determining accompanying information as in the embodiment of the invention. The computer readable medium of the present invention described above may be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to electrical wiring, fiber optic cable, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be included in the electronic device or may exist alone without being incorporated into the electronic device.
The computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to determine a target object to be accompanied, query track data of each track point of the target object within a set time range based on unique information of the target object, divide the track points into a set number of accompanying areas based on the track data, query accompanying objects that appear in common with the target object within at least two accompanying areas within the set time range, acquire accompanying track data of each accompanying object, determine accompanying rates corresponding to each accompanying object based on the accompanying track data, and determine the accompanying track data and the accompanying rates as accompanying information.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic that may be used include Field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (8)
1. A method for determining accompanying information, comprising:
determining an accompanied target object, and inquiring track data of each track point of the target object within a set time range according to unique information of the target object;
Dividing the track points into a set number of accompanying areas according to the track data, and inquiring the accompanying objects which co-occur with the target object in at least two accompanying areas within the set time range;
The method comprises the steps of obtaining accompanying track data of each accompanying object, determining a target accompanying area which is coexistent with the target object according to the corresponding accompanying track data for each accompanying object, determining accompanying time which is coexistent with the target object according to the corresponding accompanying track data for each accompanying object, taking the sum of a preset intermediate value and a preset added value of the target accompanying area corresponding to the accompanying object as a new intermediate value if the accompanying time exceeds a set time threshold value, obtaining a threshold value of each preset accompanying area, taking the quotient of the sum of the intermediate values and the sum of the threshold values as the accompanying rate corresponding to the accompanying object, and determining the accompanying track data and the accompanying rate as the accompanying information, wherein one intermediate value and one threshold value are preset for each accompanying area, the intermediate value is < threshold value, and one numerical value is preset as the added value.
2. The method of claim 1, wherein dividing the trajectory points into a set number of companion regions based on the trajectory data comprises:
determining the track radius of the track point, and expanding the track point into a track area;
Dividing the track areas according to the set number, and determining the accompanying areas of the set number;
and determining the accompanying area where each track point is located according to the track data.
3. The method of claim 2, wherein determining the trajectory radius of the trajectory point, expanding the trajectory point into a trajectory region, comprises:
expanding each track point into a circular area according to the track radius;
Supplementing a circular region set of each track point, and determining a rectangular region containing the circular region set as the track region.
4. The method of claim 1, wherein querying companion objects that co-occur with the target object in at least two companion areas over the set time horizon comprises:
Taking the accompanying areas as query conditions, and acquiring objects which coexist with the target object in the set time range in each accompanying area;
An object co-occurring with the target object in at least two companion regions is determined as the companion object.
5. The method of claim 1, wherein after determining the companion trajectory data and companion rate as the companion information, further comprising:
and arranging the accompanying information in a reverse order according to the magnitude of the accompanying rate.
6. A concomitant information determination apparatus, comprising:
The track data query module is used for determining an accompanied target object, and querying track data of each track point of the target object within a set time range according to unique information of the target object;
The companion object inquiry module is used for dividing the track points into a set number of companion areas according to the track data and inquiring companion objects which co-occur with the target object in at least two companion areas within the set time range;
The system comprises a companion information determining module, a companion information processing module and a companion information processing module, wherein the companion information determining module is used for obtaining companion track data of each companion object, determining a target companion area which is commonly appeared with the target object according to the corresponding companion track data for each companion object, determining the companion time which is commonly appeared with the companion object and the target object according to the corresponding companion track data for each companion object, setting the sum of a preset intermediate value and a preset additional value of the target companion area corresponding to the companion object as a new intermediate value if the companion time exceeds a set time threshold, obtaining a threshold value of each preset companion area, setting the quotient of the sum of the intermediate values and the sum of the thresholds as the companion rate corresponding to the companion object, and determining the companion track data and the companion rate as the companion information, wherein one intermediate value and one threshold value are preset for each companion area, and the intermediate value is < threshold value and one value is preset as the additional value.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method of determining accompanying information as claimed in any one of claims 1 to 5 when the program is executed.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processing device, implements a method of determining accompanying information as claimed in any one of claims 1-5.
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| PCT/CN2022/078543 WO2023029413A1 (en) | 2021-09-02 | 2022-03-01 | Method and apparatus for determining accompanying information, and device and storage medium |
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| CN116680605A (en) * | 2023-04-28 | 2023-09-01 | 浙江省公安厅 | An Implicit Adjoint Recognition Method Based on Depth Trajectory Representation |
| CN116450878B (en) * | 2023-06-15 | 2023-09-05 | 北京瑞莱智慧科技有限公司 | Activity track determining method, activity track determining device, computer equipment and readable storage medium |
| CN117062009B (en) * | 2023-10-11 | 2024-01-23 | 北京艾瑞数智科技有限公司 | A method, device, equipment and storage medium for identifying accompanying trajectories |
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