KR102731902B1 - Cloud based content recommend method - Google Patents

Abstract

The present invention relates to a cloud-based content recommendation method capable of recommending various types of related content to other users, regardless of the format of the content, based on keywords extracted from content stored in a cloud server. The present invention may include a step of storing content in a cloud folder designated by a user in any one of the data formats of a memo, a link, a photo, and a document, a step of deriving a keyword using the selected content when any one of the stored contents is selected and a function prepared in advance for the selected content is executed, and a step of displaying recommended content related to the derived keyword on a screen during the execution of the function.

Description

Cloud-based content recommendation method {Cloud-based content recommend method}

The present invention relates to a cloud-based content recommendation method, and more specifically, to a cloud-based content recommendation method that stores contents of different data types in a cloud server, and recommends various types of related contents regardless of the data type of the contents based on keywords extracted from the contents stored in the cloud server.

Recently, various platforms that provide information to users have been formed, and users have become accustomed to searching for the information they want through content uploaded by individuals as well as official information providers. In addition, individuals share not only content related to their personal daily lives, such as product reviews, travel destinations, and restaurant reviews, but also professional knowledge and opinions with many people through their personal SNS (Social Network Service). Accordingly, users obtain necessary information or share opinions through content uploaded to various platforms.

However, since the activities of such users on the platform can only be confirmed on individual platforms, users cannot check the information they have checked and collected on multiple platforms at once. In addition, the information that users have checked may not be in one field but may include information in various fields such as finance, shopping, entertainment, society, and culture, so users must remember the platform or the location where it was saved in order to check the information scattered across each platform.

That is, platforms provide information and provide some functions that allow users to utilize it, but users who utilize multiple platforms cannot check a large amount of information at once.

In addition, if a user wants to share content on the platform with an acquaintance, he or she must select the content on the platform one by one and share it, which makes it difficult to share a large amount of content or to share with multiple people at once.

Meanwhile, technology is being developed to analyze content selected by users through algorithms and recommend similar content. This technology to recommend similar content is mainly used in video streaming platforms.

However, in this case, since similar content is recommended based on keywords searched by users to watch videos and tag keywords directly entered by content creators in posts, there is a problem that the closeness with the actual recommended content is low if there are no tags entered by creators or search keywords are unclear. In addition, there is a disadvantage in that it is limited to only video content.

Republic of Korea Patent Publication No. 10-1305535 (10-1305535)

The problem to be solved by the present invention is to provide a cloud-based content recommendation method capable of storing different types of content in a cloud server and recommending various types of related content regardless of the format of the content based on keywords extracted from the content stored in the cloud server.

In a method for recommending related content of a cloud-based application running on a computing device according to one embodiment of the present invention, the method may include: a step in which a registration module stores content in a cloud folder specified by a user in the data format of any one of a memo, a link, a photo, and a document; a step in which, when any one of the stored contents is selected and a function prepared in advance for the selected content is executed, a step in which a detection module derives a keyword using the selected content; and a step in which, during execution of the function, a recommendation module outputs recommended content related to the derived keyword on a screen.

The above cloud folder can be divided into a personal folder that only authenticated users can access, and a shared folder that other users of the user's designated contacts can also access.

The above detection module can extract keywords from words obtained by parsing text included in the content when the selected content is a memo or document.

The above detection module can, if the selected content is a link, derive a keyword from tag information of the content connected to the link, and if the selected content is a photo, derive a keyword from meta information included in the photo.

If the above selected content is stored in a shared folder, one of the pre-prepared functions may be commenting and replying to the above selected content.

If the selected content is stored in a shared folder, one of the pre-prepared functions may be chatting with at least one of the users permitted to access the selected content.

The above recommendation module can display on the screen recommended content corresponding to a verb mentioned after the keyword or a similar keyword mentioned in the chat message.

According to an embodiment of the present invention, contents of different types are stored in a cloud server, and various types of related contents can be recommended regardless of the format of the contents based on keywords extracted from the contents stored in the cloud server.

FIG. 1 is a block diagram of a cloud-based content recommendation system (100) according to Embodiment 1 of the present invention.
FIG. 2 is a flowchart of a cloud-based content recommendation method according to Embodiment 2 of the present invention.
Figures 3 to 8 are screens implemented in the software of embodiments 1 and 2.

Hereinafter, several embodiments of the present invention will be described in detail using drawings. However, this is not intended to limit the present invention to any specific embodiment, and it should be understood that all transformations, equivalents, and substitutions that include the technical idea of the present invention are included in the scope of the present invention.

In this specification, singular expressions include plural expressions unless the context clearly indicates otherwise.

When it is stated in this specification that a component "has" or "comprises" a sub-component, it is intended that the other component may be included, rather than excluding the other component, unless otherwise specifically stated.

The terms “Unit,” “Module,” and “Component” in this specification mean a unit that processes at least one function or operation, and may be implemented by hardware, software, or a combination of hardware and software.

FIG. 1 is a block diagram of a cloud-based content recommendation system (100) according to Embodiment 1 of the present invention.

The system (100) of Example 1 can be implemented in the form of software such as an application running on a computing device, where software refers to an app running on a mobile terminal such as a smartphone or tablet PC running on Google's Android or Apple's IOS, or an application program or script program running on a computing terminal such as a notebook PC or desktop PC running on Microsoft's Windows or Google's Chrome OS, or a server device, or a general term for other computer programs that operate similarly to apps, applications, or scripts.

The computing device may be one of a laptop computer, a smart phone, a tablet PC, a personal digital assistant (PDA), an enterprise digital assistant (EDA), a mobile Internet device (MID), and an e-book, which is a terminal used by the user.

The system (100) of Example 1 includes a registration module (110), a detection module (120), and a recommendation module (130).

The registration module (110) stores at least one content selected by the user in a cloud folder created by the user. The content stored in the folder is stored in one of the data formats of a memo, link, photo, or document.

A cloud folder is created at least once by a user. The cloud folder is linked to a cloud server, and the content is stored on the cloud server. Data stored in the cloud folder can only be viewed by authenticated users (e.g., registered and logged in).

Cloud folders can be created as personal folders that only authenticated users can access, and shared folders that other users of the user's designated contacts can access. Personal folders are folders that can only be used by the person who has installed the software and registered as a member and has been authenticated. Shared folders are folders created by authenticated members for the purpose of sharing stored data with other users. Multiple personal folders and shared folders can be created.

When a user selects a designated person (i.e., another user) through a contact stored in a computing device as a method for allowing access to a shared folder, the registration module (110) can send a link to the designated person through a text message or messenger application to allow access to the shared folder. The designated person who receives the link from the user can install software through the link and access the shared folder after authenticating himself/herself.

Other users who have access to the shared folder can check the data stored in the shared folder, but they can only read the data and cannot edit or delete the data.

Among the contents stored in the folder, memos are texts written in a preset format and entered by the user. The registration module (110) can store texts (i.e. memos) directly written by the user through the keyboard or keypad provided on the computing device in the folder, or can store texts copied through the computing device and pasted into the folder.

Among the contents stored in the folder, links refer to a standard that indicates the location of files on servers that provide various services for web documents, and the registration module (110) stores links in the folder in the form of URLs.

Among the contents stored in the folder, photos are photo data stored in a separate device, i.e., a memory or SD card, equipped with the user's computing device, and the registration module (110) uploads the photos stored in the computing device and stores them in the folder. The photos stored in the computing device may be photos taken directly by the user through a camera equipped with the computing device, photos captured from a web page screen, or photos downloaded from the Internet. In Example 1, it is defined as a photo, but it may also include a video.

Among the contents stored in the folder, documents are files stored in formats such as PDF, HWP, DOC, and EXECL, and the registration module (110) uploads document files stored in the computing device and stores them in the folder.

The detection module (120) derives a keyword using the selected content when one of the contents stored in the folder is selected by the user and a pre-prepared function is executed for the selected content.

Here, the pre-prepared function may be a function to comment and reply to the selected content, or a chat with at least one other user who is permitted to access the selected content. Also, the content selected by the user may mean that the content is selected when the function to comment and reply to the content is performed.

The chat function can be executed when a user attempts to chat with another user by using the Add Chat button on a page where selected content is posted. In this case, a portion of the entire screen may be displayed as a chat screen, and the remaining portion may display information about the selected content.

The folder from which keywords are derived in the detection module (120) may be a shared folder because at least one of the functions of chatting, commenting, and replying must be executed.

The detection module (120) extracts keywords from at least one of the contents stored as notes, links, photos, and documents in a shared folder when chat, reply, and comment functions are performed on the contents.

As an example of a detection module (120) deriving a keyword, if data stored in a shared folder is a link and another user enters a reply or comment on the page where the link is stored (or posted), the detection module (120) can derive a keyword from tag information of the content linked to the link or derive a keyword using a description text of the content linked to the link.

For example, if “coffee in December with snow” is entered in the tag information of the content connected to the link or the description text for the content, the detection module (120) can derive directly related keywords such as snow, December, and coffee, or similar keywords such as snow, winter, cafe, and dessert.

Another example of the detection module (120) deriving keywords is when data stored in a shared folder is a photo and another user enters a reply or comment on the page where the photo is stored (or posted), the detection module (120) analyzes the meta information contained in the photo to derive related keywords. For example, the meta information contained in the photo includes information such as the location, date, and time at which the photo was taken, and the detection module (120) can derive keywords such as season and region through the meta information. In addition, the detection module (120) can also derive keywords using tags entered by the user when saving the photo and a description of the photo.

As another example of the detection module (120) deriving keywords, if data stored in a shared folder is a document file and another user enters a reply or comment on the page where the document file is stored (or posted), the detection module (120) can open the document file and parse the text in the document file or analyze meta information included in an image in the document file to derive keywords.

As another example of how the detection module (120) derives keywords, if data stored in a shared folder is a memo and another user enters a reply or comment on the page where the memo is stored (or posted), the detection module (120) can derive keywords by parsing the text included in the memo.

The recommendation module (130) outputs recommended content related to keywords derived from the detection module (120) on the screen while at least one of chat, comment, and reply functions for the selected content is being executed.

Recommended content is content associated with keywords derived by the detection module (120) from content posted on the screen (i.e., content selected by the user), and may be data stored in a shopping site, blog site, social network service, video streaming site, search engine, etc.

If the keywords derived from the content are “snow,” “December,” “coffee,” and “cafe,” the recommendation module (130) can output at least one content among a video, blog review, and cafe location related to a good cafe to visit in winter as recommended content.

The recommendation module (130) can output recommended content to at least one of the screens of the user entering the comment or reply or another user when comments and replies are being posted on a page where notes, links, photos, and documents are saved (i.e., stored), and when the user and another user are chatting, the recommended content can be output to the user's screen and the other user's screen.

In this way, the recommendation module (130) of Example 1 recommends related content for all data regardless of data format (e.g., memo, link, photo, document), not just video.

For example, the recommendation module (130) may display recommended content in a pop-up form on a part of the screen, and in this case, the recommended content may be output in a manner that switches to the corresponding recommended content screen when clicked by the user or another user.

The recommendation module (130) may output other contents with the same keywords and similar keywords as the selected contents, stored in the same folder or in a different folder, as recommended contents when at least one of the functions of chatting, commenting, and replying is executed for the selected contents.

For example, if at least one of the functions of chat, comment, and reply is executed for the selected content, and the keywords derived from the selected content are “December” and “cafe,” the content from among the other contents stored in the same folder or a different folder from which the keywords “December” and “cafe” are derived is output as the recommended content.

The recommendation module (130) outputs recommended content associated with a keyword derived from the detection module (120) or a similar keyword when the keyword is mentioned (i.e., entered) in a chat message, comment, or reply.

For example, if at least one of chat, comment, and reply functions is executed for selected content, and “December” and “cafe” are mentioned by the user or another user in the chat, comment, and reply, the recommendation module (130) may output at least one content among a video about a cafe that is good to visit in winter (e.g., content of a video streaming site), a blog review, and a cafe location as recommended content.

In addition, the recommendation module (130) may output, as recommended content, content from which the same keyword or similar keyword is derived among contents stored in another folder or the same folder, if a keyword or similar keyword derived from the detection module (120) is mentioned (i.e., entered) among chat messages, comments, and replies. For example, the recommendation module (130) may output, as recommended content, content from which the keywords “December” and “cafe” are derived among contents stored in the same folder or another folder.

Meanwhile, the recommendation module (130) may also display on the screen recommended content corresponding to a verb mentioned after the keyword or similar keyword derived from the detection module (120) when the keyword or similar keyword is mentioned (i.e., entered) in a chat message, comment, or reply.

For example, if the selected content is a picture of an idol (e.g., Fin.K.L.), the recommendation module (130) may output at least one of the following recommended content matching “Fin.K.L.’s new song is really good, have you heard it?”: a post on a video platform where the sound source of the new song is played, a website where the sound source can be downloaded, or a post on another platform promoting the new song. In addition, the recommendation module (130) may output recommended content matching “Fin.K.L.’s new song is really good, have you heard it?”: a post on a video platform where the sound source of the new song is played, a website where the sound source can be downloaded, or a post on another platform promoting the new song.

FIG. 2 is a flowchart of a cloud-based content recommendation method according to Embodiment 2 of the present invention.

The modules of Example 2 can be implemented in the form of software such as an application running on a computing device, where the term “software” refers to an app running on a mobile terminal such as a smartphone or tablet PC running on Google’s Android or Apple’s IOS, or an application program or script program running on a computing terminal such as a notebook PC or desktop PC running on Microsoft’s Windows or Google’s Chrome OS, or a server device, or a general term for other computer programs that operate similarly to apps, applications, or scripts.

The computing device may be one of a laptop computer, a smart phone, a tablet PC, a personal digital assistant (PDA), an enterprise digital assistant (EDA), a mobile Internet device (MID), and an e-book, which is a terminal used by the user.

The method of Example 2 includes a step of storing content (S110), a step of deriving keywords using selected content (S120), and a step of displaying recommended content on a screen (S130).

The step of saving content (S110) is that the registration module saves at least one content selected by the user in a cloud folder designated by the user. The content saved in the folder is saved in one of the data formats of a memo, link, photo, or document.

A cloud folder is created at least once by a user. The cloud folder is linked to a cloud server, and the content is stored on the cloud server. Data stored in the cloud folder can only be viewed by authenticated users (e.g., registered and logged in).

Cloud folders can be created as personal folders that only authenticated users can access, and shared folders that other users of the user's designated contacts can access. Personal folders are folders that can only be used by the person who has installed the software and registered as a member and has been authenticated. Shared folders are folders created by authenticated members for the purpose of sharing stored data with other users. Multiple personal folders and shared folders can be created.

When a user selects a designated person (i.e., another user) through a contact stored on the computing device as a method for allowing access to a shared folder, the registration module can send a link to the designated person via a text message or messenger application to allow access to the shared folder. The designated person who receives the link from the user can install software through the link and access the shared folder after authenticating himself/herself.

Other users who have access to the shared folder can check the data stored in the shared folder, but they can only read the data and cannot edit or delete the data.

Among the contents saved in the folder, the memo is text written in a preset format and entered by the user. The registration module can save text (i.e., memo) directly written by the user through the keyboard or keypad provided on the computing device to the folder, or can save text copied through the computing device and pasted into the folder.

Among the contents saved in the folder, links are a standard that indicates the location of files on servers that provide various services for web documents, and the registration module saves links in the folder in the form of URLs.

Among the contents stored in the folder, photos are photo data stored in a separate device, i.e., a memory or SD card, equipped with the user's computing device, and the registration module uploads the photos stored in the computing device and stores them in the folder. The photos stored in the computing device may be photos taken directly by the user through a camera equipped with the computing device, photos captured from a web page screen, or photos downloaded from the Internet. In Example 1, it is defined as a photo, but it may also include a video.

Among the contents saved in the folder, documents are files saved in formats such as PDF, HWP, DOC, and EXECL, and the registration module uploads document files saved in the computing device and saves them in the folder.

The step (S120) of deriving keywords using selected content is when a detection module selects one of the contents stored in a folder by the user and executes a function prepared in advance for the selected content, the detection module derives keywords using the selected content.

Here, the pre-prepared function may be a function to comment and reply to the selected content, or a chat with at least one other user who is permitted to access the selected content. Also, the content selected by the user may mean that the content is selected when the function to comment and reply to the content is performed.

The chat function can be executed when a user attempts to chat with another user by using the Add Chat button on a page where selected content is posted. In this case, a portion of the entire screen may be displayed as a chat screen, and the remaining portion may display information about the selected content.

The folder from which keywords are derived in the detection module may be a shared folder, as at least one of the following functions must be executed: chat, comment, and reply.

The detection module extracts keywords from the content when chat, reply, and comment functions are performed on at least one of the contents stored as notes, links, photos, and documents stored in the shared folder.

As an example of a detection module deriving keywords, if data stored in a shared folder is a link and another user enters a reply or comment on the page where the link is stored (or posted), the detection module can derive keywords from tag information of the content linked to the link or derive keywords using descriptive text about the content linked to the link.

For example, if the tag information of the content linked to the link or the description text for the content contains “coffee in December when it snows,” the detection module can derive directly related keywords such as snow, December, and coffee, or similar keywords such as snow, winter, cafe, and dessert.

When the data stored in the shared folder is a photo and another user enters a reply or comment on the page where the photo is saved (or posted), the detection module analyzes the metadata contained in the photo to derive related keywords. For example, the metadata contained in the photo includes information such as the location, date, and time the photo was taken, and the detection module can extract keywords such as season and region through the metadata. In addition, the detection module can derive keywords using tags entered by the user when saving the photo and descriptions of the photo.

When data stored in a shared folder is a document file and another user enters a reply or comment on the page where the document file is stored (or posted), the detection module can open the document file and parse the text within the document file or analyze the meta information contained in the image within the document file to derive keywords.

If the data stored in the shared folder is a note and another user enters a reply or comment on the page where the note is stored (or posted), the detection module can parse the text contained in the note to derive keywords.

The step of displaying recommended content on the screen (S130) is to display recommended content related to keywords derived from the detection module while at least one of chat, comment, and reply functions is executed for the selected content by the recommendation module.

Recommended content is content related to keywords derived by a detection module from content posted on the screen (i.e. content selected by the user), and may be data stored on shopping sites, blog sites, social network services, video streaming sites, search engines, etc.

If the keywords derived from the content are “snow,” “December,” “coffee,” and “cafe,” the recommendation module can output at least one content among videos, blog reviews, and cafe locations related to cafes that are good to visit in winter as recommended content.

The recommendation module can display recommended content on at least one of the screens of the user entering a comment or reply or another user when comments and replies are being made on a page where notes, links, photos, and documents are saved (i.e., stored), and can display recommended content on the user's screen and the other user's screen when the user and another user are chatting.

In this way, the recommendation module of Example 2 recommends related content for all data regardless of data format (e.g., memo, link, photo, document), not just videos.

For example, the recommendation module may display recommended content in the form of a pop-up on a part of the screen, and in this case, the recommended content may be output in a way that switches to the recommended content screen when clicked by the user or another user.

The recommendation module may output other content with the same keywords and similar keywords as the selected content, stored in the same folder or in a different folder, if at least one of the functions of chatting, commenting, and replying is executed for the selected content.

For example, if at least one of the functions of chat, comment, and reply is executed for the selected content, and the keywords derived from the selected content are “December” and “cafe,” the content from among the other contents stored in the same folder or a different folder from which the keywords “December” and “cafe” are derived is output as the recommended content.

The recommendation module outputs recommended content associated with a keyword or similar keyword derived from the detection module when the keyword or similar keyword is mentioned (i.e., entered) in a chat message, comment, or reply.

For example, if at least one of chat, comment, and reply functions is executed for selected content, and “December” and “cafe” are mentioned by the user or another user in the chat, comment, or reply, the recommendation module may output at least one content among a video about a cafe (e.g., content from a video streaming site), a blog review, and a cafe location related to a cafe that is good to visit in winter as recommended content.

In addition, the recommendation module may output contents from which the same keyword or similar keyword is derived among contents stored in different folders or the same folder as recommended contents when keywords or similar keywords derived from the detection module are mentioned (i.e., input) among chat messages, comments, and replies. For example, the recommendation module may output contents from which the keywords “December” and “cafe” are derived among contents stored in the same folder or a different folder as recommended contents.

Meanwhile, the recommendation module may also display recommended content corresponding to a verb mentioned after a keyword or similar keyword derived from the detection module is mentioned (i.e., entered) in a chat message, comment, or reply.

For example, if the selected content is a photo of an idol (e.g., Fin.K.L.), the recommendation module can output at least one of the following recommended contents matching “Fin.K.L.’s new song is really good. Have you listened to it?”: a post on a video platform where the new song’s audio is played, a website where the audio is available for download, or a post on another platform promoting the new song. In addition, the recommendation module can also output recommended contents matching “Fin.K.L.’s new song is really good. Have you listened to it?”: a post on a video platform where the new song’s audio is played, a website where the audio is available for download, or a post on another platform promoting the new song.

Figures 3 to 8 are screens implemented in the software of embodiments 1 and 2.

As shown in Figure 3, the software presents items on the screen of the computing device that allow you to save notes, links, photos, and files.

Users can save content by selecting one of the items presented by the software depending on the type of content they wish to save.

As shown in Fig. 4, the software presents a screen for selecting another user based on contacts to allow access to the shared folder created by the user. The user can select a designated person (i.e., another user) through contacts stored on the computing device and send a link to the designated person via text message or messenger application to allow access to the shared folder. The designated person who receives the link from the user can install the software through the link and access the shared folder after identity verification.

As shown in Figure 5, the software sets the background of a folder to data extracted from the contents stored in that folder.

For example, if a link is stored in a folder and the content linked to the link is a web page, the image included in the web page is set as the background of the folder. This allows users to intuitively check what content the link is linked to without having to access the link.

As shown in Figure 6, if a link is stored in a folder and the content linked to the link is a video streaming page, the software captures an image of the screen at a preset playback time during video streaming and sets it as the background of the folder. This allows the user to intuitively check which content the link is linked to without having to access the link.

As shown in Figure 7, the software presents the content saved by the user by sorting it by type. For example, the software presents the number of contents saved in each of notes, links, photos, and files.

The software may also present the contents in chronological order. Additionally, the software may provide a list of other users who are permitted access to each shared folder.

As shown in Fig. 8, the software executes the comment and reply function on a content screen selected by a user or another user, and if a keyword or similar keyword derived from the content is mentioned (i.e., entered) in a comment or reply, it outputs recommended content associated with the keyword.

For example, if at least one of chat, comment, and reply functions is executed for selected content, and “December” and “cafe” are mentioned by the user or another user in the chat, comment, and reply, the software may output at least one content of a video, blog review, or cafe location related to a good cafe to visit in winter as recommended content.

Although the present invention has been described above with reference to several embodiments thereof, it will be understood by those skilled in the art that various modifications and changes may be made to the present invention without departing from the spirit and scope of the present invention as set forth in the claims below.

110: Registration module
120: Detection module
130: Recommended Module
S110: Steps to save content
S120: Step of deriving keywords using selected content
S130: Step for displaying recommended content on the screen

Claims (7)

A method for recommending related content for a cloud-based application running on a computing device,
When a user selects any one of the contents of a note, link, photo, or document, the registration module saves the selected content to a specific cloud folder designated by the user;
When a user selects one content from the cloud folder and another user is specified to start chatting, the detection module derives a keyword from the selected content; and
The recommendation module includes a step of displaying recommended content related to the above-described keywords on the screen,
The above cloud folder is characterized in that it is a shared folder accessible to both the above user and the other user.
A cloud-based content recommendation method. delete In the first paragraph,
A cloud-based content recommendation method, characterized in that the above detection module derives keywords from words obtained by parsing text included in the content when the selected content is a memo or document. In the first paragraph,
The above detection module,
A cloud-based content recommendation method characterized in that, if the selected content is a link, keywords are derived from tag information of content linked to the link, and if the selected content is a photo, keywords are derived from meta information included in the photo. delete delete In the first paragraph,
The above recommended module is,
A cloud-based content recommendation method characterized in that, when the above-described keyword or a similar keyword is mentioned during the above-described chat message, recommended content corresponding to a verb mentioned after the mentioned keyword is displayed on the screen.