WO2024090726A1 - Procédé de recommandation d'image sur messagerie, support d'enregistrement et dispositif informatique - Google Patents

Procédé de recommandation d'image sur messagerie, support d'enregistrement et dispositif informatique Download PDF

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Publication number
WO2024090726A1
WO2024090726A1 PCT/KR2023/010496 KR2023010496W WO2024090726A1 WO 2024090726 A1 WO2024090726 A1 WO 2024090726A1 KR 2023010496 W KR2023010496 W KR 2023010496W WO 2024090726 A1 WO2024090726 A1 WO 2024090726A1
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Prior art keywords
video
data
user
messenger
recommendation
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PCT/KR2023/010496
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English (en)
Korean (ko)
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조현지
김경진
전희영
양어진
Original Assignee
라인플러스 주식회사
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Publication of WO2024090726A1 publication Critical patent/WO2024090726A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/73—Querying
    • G06F16/732—Query formulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/73—Querying
    • G06F16/732—Query formulation
    • G06F16/7343—Query language or query format
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/73—Querying
    • G06F16/735—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/73—Querying
    • G06F16/738—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/50—Business processes related to the communications industry
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/04—Real-time or near real-time messaging, e.g. instant messaging [IM]
    • H04L51/046—Interoperability with other network applications or services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/07—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail characterised by the inclusion of specific contents
    • H04L51/10—Multimedia information

Definitions

  • This disclosure relates to a video recommendation method in a messenger, a recording medium, and a computing device. More specifically, it relates to video recommendation methods, recording media, and computing devices that help users easily select content to share through messengers.
  • the user In order to share video content through a messenger, the user must individually check a large amount of videos stored in the video storage of his device with a built-in messenger, such as a video album folder or gallery folder, and select the video to share. For efficient confirmation, the user can create a separate shared space, such as a shared folder, on the device or messenger, and save the images of interest in the video storage in advance into the shared space, thereby significantly reducing the amount of images to be checked. This method also involves the inconvenience of requiring the user to check and move a large amount of images through the image storage.
  • a built-in messenger such as a video album folder or gallery folder
  • the purpose of the present disclosure is to provide a video recommendation method and computing device that contribute to users easily selecting content to share via messenger.
  • the present disclosure aims to provide a computer-readable recording medium on which a program for executing the method on a computing device is recorded.
  • a method of recommending an image in a messenger performed by a computing device including a processor includes the steps of generating additional information of an image managed in the messenger and tagging it; registering the video tagged with the additional information in a recommendation list of the messenger; In response to a sharing request from a user participating in the chat room, recommending at least one video registered in the recommendation list based on recommendation standard information of the chat room and the additional information; and in response to the user's selection of the recommended video, sharing the selected video in the chat room.
  • the additional information may have detailed data including at least one of time data of the image, location data of the image, and object data having information identifying at least one object of the image. You can.
  • the object data is managed so that a rough identifier that classifies each object included in the video is associated with the object, profile data of a user who participated in the chat room, and an object that is related to the user.
  • the object data may be managed to associate a detailed identifier from which at least one of the profile data and the name data is extracted with the recognized object. .
  • the additional information has shared related data including at least one of history data that manages the sharing history of the video and keyword data that manages keywords used to select the shared video.
  • the history data includes a sharing history of videos shared in at least one of the current chat room in which the user participates and another chat room in which the user participates
  • the keyword data includes at least one of the current chat room and the other chat room. may include keywords used to select the shared video.
  • the keyword data includes related data related to selection of the shared video among conversation data exchanged between users of the chat room and the user searches for the shared video through the messenger. and at least one of query data including a query used to do so, and the related data and the query data may be inferred through machine learning for the conversation data and the query.
  • the sharing request may be either a video sharing request by the user using a menu of the chat room or a video sharing request by a keyword entered into a message input window of the chat room.
  • the step of recommending the video is based on the recommendation criteria information according to the keyword, to the device video stored in the computing device and a search engine.
  • the method may further include adding the external content to at least one of the video list and the recommendation list managed by the messenger in response to the user's request.
  • the recommendation standard information includes at least one of sharing standard information according to a predetermined condition, context information of the chat room, or a keyword entered by the user for the sharing request, and the context
  • the information may include at least one of user linkage information related to users participating in the chat room and conversation information extracted from conversation data of the chat room.
  • the step of recommending the video includes: preferentially searching for videos registered in the recommendation list and recommending the videos;
  • searching for and presenting the device image matching the recommendation standard information in the David video stored in the computing device In response to the image matching the recommendation standard information not being searched for in the recommendation list, searching for and presenting the device image matching the recommendation standard information in the David video stored in the computing device; And in response to the device image not being searched, it may include searching and presenting an image matching the recommendation criteria information by a search engine.
  • generating and tagging additional information of an image managed by the computing device and adding the video tagged with the additional information to at least one of a video list managed by the messenger and the recommendation list at the request of the user.
  • a computing device that implements instructions, the computing device comprising: a memory storing at least one instruction; and a processor executing the at least one instruction stored in the memory.
  • the processor generates and tags additional information of the video managed in the messenger, registers the video tagged with the additional information in the recommended list of the messenger, and in response to a sharing request from a user participating in the chat room, It is configured to recommend at least one video registered in the recommendation list based on recommendation standard information and the additional information, and to share the selected video in the chat room in response to the user's selection of the recommended video.
  • a computer-readable recording medium may include a computer program that executes the image recommendation method in a messenger according to the present disclosure.
  • a video recommendation method that helps users easily select content to share through a messenger can be provided.
  • a computing device that performs the method may be provided.
  • a computer-readable non-transitory recording medium recording a program for executing the above method on a computing device.
  • the user's convenience in sharing content can be increased by analyzing conversation characteristics between users through machine learning and efficiently selecting and recommending content suitable for conversation intent.
  • FIG. 1 is a diagram illustrating a system in which a video recommendation method in a messenger is implemented according to an embodiment of the present disclosure.
  • FIGS. 2 and 3 are block diagrams illustrating a user device and a server that implement a video recommendation method in a messenger according to an embodiment of the present disclosure.
  • Figure 4 is a flowchart of a video recommendation method in a messenger according to an embodiment of the present disclosure.
  • Figure 5 is a flow chart regarding the generation and tagging of additional information for an image.
  • Figures 6 to 8 are diagrams showing an example of video recommendation implemented in a messenger.
  • Figure 9 is a diagram showing another example of video recommendation implemented in a messenger.
  • Figures 10 and 11 are diagrams showing another example of video recommendation implemented in a messenger.
  • Figure 12 is a flowchart of a method for adding external content to the video list of a messenger.
  • FIG. 13 is a diagram illustrating an additional inquiry about external content according to FIG. 12.
  • a component when a component is said to be “connected,” “coupled,” or “connected” to another component, this is not only a direct connection relationship, but also an indirect connection relationship in which another component exists in between. It may also be included.
  • a component when a component is said to “include” or “have” another component, this does not mean excluding the other component, but may further include another component, unless specifically stated to the contrary. .
  • first and second are used only for the purpose of distinguishing one component from other components, and do not limit the order or importance of the components unless specifically mentioned. Therefore, within the scope of the present disclosure, a first component in one embodiment may be referred to as a second component in another embodiment, and similarly, the second component in one embodiment may be referred to as a first component in another embodiment. It may also be called.
  • a or B “at least one of A and B”, “at least one of A or B”, “A, B or C”, “at least one of A, B and C”, and “A , B, or C or a combination thereof, each of which means one of the items listed together with that phrase, or any possible combination thereof. may include.
  • distinct components are intended to clearly explain each feature, and do not necessarily mean that the components are separated. That is, a plurality of components may be integrated to form one hardware or software unit, or one component may be distributed to form a plurality of hardware or software units. Accordingly, even if not specifically mentioned, such integrated or distributed embodiments are also included in the scope of the present disclosure.
  • components described in various embodiments do not necessarily mean essential components, and some may be optional components. Accordingly, embodiments consisting of a subset of the elements described in one embodiment are also included in the scope of the present disclosure. Additionally, embodiments that include other components in addition to those described in various embodiments are also included in the scope of the present disclosure.
  • a network may be a concept that includes both wired and wireless networks.
  • the network may refer to a communication network in which data exchange between devices, systems, and devices can be performed, and is not limited to a specific network.
  • the computing device or device may be a mobile device such as a smartphone, tablet PC, wearable device, laptop, or HMD (Head Mounted Display).
  • the device may be a fixed device, such as a PC or a home appliance with a display function.
  • the computing device or device may be a computing device capable of operating as a server or an Internet of Things (IoT) device. That is, the device in this specification may refer to devices capable of performing the method according to the present disclosure, and is not limited to a specific type.
  • IoT Internet of Things
  • FIG. 1 is a diagram illustrating a system in which a video recommendation method in a messenger is implemented according to an embodiment of the present disclosure.
  • the system according to the present disclosure may include one or more user devices 100a, 100b, and 100c connected through a network 300 and a server 200.
  • Each of the user devices 100a to 100c may be referred to as a client or a user terminal, and may connect to the server 200 through the network 300 to transmit and receive data with other user devices or the server.
  • the video recommendation method according to the present disclosure can be performed using a messenger service provided in connection with various online services.
  • Messenger services may be communication services provided by instant messenger providers, social media, community sites, online games, portal sites, shopping malls, etc.
  • instant messenger providers can provide basic functions of messenger services, and social media, community sites, online games, etc. can provide messenger services for users' communication in addition to the basic functions of each service.
  • the messenger service not only includes communication through an instance messenger, but may also include communication services additionally provided by various services in a broad sense. If the video recommendation method through communication between users according to the present disclosure is at least a service that is realized, the service can be considered to have implemented a messenger service regardless of its basic form.
  • the instant messenger service will be described as an example of a messenger service in which the video recommendation method according to the present disclosure is implemented, but application to various services in which the messenger service is implemented regardless of the basic form is not excluded.
  • a client module for using the messenger service may be installed in each of the user devices 101, 102, and 103. Additionally, a server module to support a messenger service may be installed in the server 200.
  • an application installed on a user device may mean a client module installed on each of the user devices 101, 102, and 103 to use an instant messenger service.
  • the application may include functionality to automatically recommend and share content in communications between users.
  • the server 200 may provide services such as messenger applications.
  • a user using the service can access the server 200 providing the service by entering predetermined access information (ID and password) through the user device.
  • the server 200 can identify and authenticate the connected user through connection information received from the user device. Additionally, the server 200 may collect, accumulate, store, and retrieve information about identified users, or support data transmission and reception between identified users.
  • the server 200 may perform a function of automatically recommending and sharing content in communication between users through the application.
  • FIGS. 2 and 3 are block diagrams illustrating a user device and a server that implement a video recommendation method in a messenger according to an embodiment of the present disclosure.
  • the user device 100 may include a communication unit 110, a photographing unit 120, an input unit 130, an output unit 140, a memory 150, and a processor 160.
  • the user devices 100a to 100c may further include other components or modules related to the operation and function of the device, and are not limited to the above-described embodiments.
  • the communication unit 110 may exchange data with the server 200 or other user devices through a network.
  • the communication unit 110 may include all types of wired and wireless communication modules capable of communicating with the outside.
  • the photographing unit 120 may include all types of photographing means capable of obtaining still images or moving images of objects. Taking a smartphone as an example, the recording unit may be a camera module provided in the smartphone. Although omitted in this disclosure, the user devices 100a to 100c may further include multiple sensor modules for detecting surrounding situations, locations, and user motions in addition to the photographing unit.
  • the input unit 130 is an interface that receives user input and may be provided with various input means.
  • the input unit 130 may include an input means using a pressure sensor, a capacitive touch sensor, etc. (for example, a virtual keyboard displayed on a touch screen), a mechanical button, etc.
  • the user device 100 may obtain information detected by the sensor or input from a mechanical button as input information.
  • the input unit 130 may have a microphone that receives voice or sound.
  • the output unit 140 may output information acquired or received by the user device 100, information processed by the user device 100, etc. to the outside.
  • the output unit 140 may include, for example, a display that outputs visual information, a speaker that outputs audio information, etc.
  • the memory 150 may store and manage data generated or transmitted by an application implementing various functions of the user device 100, the processor 160, or an external request.
  • the memory 150 may store information obtained from the user, such as information obtained through the input unit 130.
  • the memory 150 may store information received from the server 200 or another user device through the communication unit 110.
  • the memory 150 may store images captured by the user device 100 or external images obtained from an external source.
  • the memory 150 may provide a storage area for storing images, and the storage area may store image data as well as unique information and additional information about the image.
  • Unique information is, for example, video format and shooting-related parameters, and the video format may be information related to the video compression method.
  • the additional information may include at least one description data used to recommend a shared video, rather than parameters required for video playback.
  • the additional information may include detailed data related to the shooting time of the image, the shooting location, and objects in the image.
  • the memory 150 can store and manage shared videos transmitted or received by a messenger application and recommended videos selected by the application.
  • the memory 150 can store and manage additional information about shared videos and recommended videos.
  • the additional information may include sharing-related data for videos that have a sharing history through a messenger application, in addition to the above-described data.
  • videos shared by a user through a messenger application are stored in a video list provided in a submenu of the messenger, and the memory 150 may provide a storage area for the video list.
  • the messenger application executes the video recommendation method according to the present disclosure, the recommended video and additional information tagged with the recommended video may be stored in the recommendation list provided in the submenu of the messenger.
  • the memory 150 may provide a storage area for the recommendation list.
  • the messenger application may provide a shared storage service for at least some data of the user device 100.
  • the memory 150 may store the video and its additional information individually acquired by the user device 100.
  • the memory 150 can store and manage images acquired from the cloud server and additional information thereof.
  • the memory 150 may embed a messenger application to implement the image recommendation method according to the present disclosure by the processor 160.
  • the memory 150 may transmit additional information about the video to the processor 160 in response to a recommendation request from the application.
  • the processor 160 may control the operation of other components within the user device 100. For example, the processor 160 may process information obtained through the input unit 130 and the communication unit 110. Additionally, the processor 160 may read and process information and applications stored in the memory 150 upon request. The processor 160 may output the processed information through the output unit 140, store it in the memory 150, or transmit it to the outside through the communication unit 110.
  • the processor 160 may generate additional information about an image captured by a user or an image content obtained from an external source and tag the image or image-related information.
  • the processor 160 may determine an image to recommend by analyzing additional information about the image managed in the memory 150 in response to a video recommendation request by the messenger application.
  • the server 200 may include a communication unit 210, a memory 220, and a processor 230.
  • the server 200 may further include other components and modules related to the operation of the server or system, and is not limited to the above-described embodiment.
  • the communication unit 210 may exchange data with a user device or another server connected to the network 300.
  • the communication unit 210 may include all types of wired and wireless communication modules capable of communicating with the outside.
  • the memory 220 may store information received from the outside through the communication unit 210. Additionally, the memory 220 may store information generated inside the server 200. For example, profile data of a user using a messenger application may be stored and managed in the memory 220. Profile data may include the user's personal information and user profile image. The profile video may be a video that the user designates as his or her representative image and registered in the application, or may be a user's video that has been confirmed to include the user among the videos that the user has accumulated and stored in the application.
  • the name data of the other object is stored in the memory (220) ) can be stored and managed.
  • Name data can be generated from user records or extracted from keywords used to share video. These keywords may be a type of shared related data.
  • the profile data and name data may be managed by the user device 100 that generates the data, and may be delivered at the request of the server 200 or another user device.
  • the processor 230 may control the operation of other components within the server 200. For example, the processor 230 may process information obtained through the communication unit 210. Additionally, the processor 230 can read and process information stored in the memory 220. The processor 230 may store the processed information in the memory 220 or transmit it to the outside through the communication unit 210.
  • the processor 230 may process a request from the user device 100 by executing a messenger application.
  • the processor 230 may implement the image recommendation method according to the present disclosure, similar to the user device 100.
  • the processor 230 may collaborate with the user device 100 to distribute and process various requests according to the video recommendation method according to the disclosure.
  • the user device 100 and/or the server 200 that implement the video recommendation method of the present disclosure may be an example of a computing device.
  • FIG 4 is a flowchart of a video recommendation method in a messenger according to an embodiment of the present disclosure.
  • the image recommendation method according to the present disclosure is performed by a computing device including at least one of the user device 100 and the server 200, and more specifically, the processor 160 and/or the server of the user device 100. It may be implemented by processor 230 of 200.
  • processor 160 and 230 will be omitted, and the process of the method will be mainly described as being performed by the user device 100.
  • the operations described below may be implemented by the server 200 that operates the messenger application, or may be performed through distributed processing of the user device 100 and the server 200.
  • the video recommendation method is mainly described as being implemented in a messenger application provided in an instant messenger service, but it can also be substantially applied in the same way to a messenger additionally provided in another service.
  • messenger application will be described interchangeably with messenger.
  • the user device 100 When a user shares a video stored in the user device 100 through a messenger, the user device 100 stores the shared video in the storage area of the messenger, and the user device 100 generates additional information about the shared video. It can be stored in the storage area.
  • the storage area may be a storage space related to a video list provided as a submenu of a messenger.
  • the video list may be prepared for each shared chat room (see 402 in FIG. 6), or may be a storage space that stores all shared videos transmitted from each chat room.
  • the video stored in the video list may be, for example, a video file or a thumbnail of the video in order to efficiently use the storage capacity of the user device 100.
  • the original image file related to the thumbnail may be stored in a certain area of the memory of the user device 100, for example, in the image storage of the device.
  • the user device 100 can transmit the video stored in the video storage through the messenger.
  • the user device 100 may generate additional information for the stored video and store the uploaded video and additional information in the video list.
  • the user device 100 may store the image in the memory 150 and generate additional information about the image.
  • additional information is generated only for images stored in the messenger and shared images, and additional information is generated for images of the user device 100 acquired through a path other than the messenger. It may not work.
  • additional information may be generated for only a portion of the image of the user device 100 based on the user's selection and settings of the device 100.
  • additional information may be generated for an image of the device 100 that matches at least some of the metadata of the image stored or shared in the messenger and the object identification data.
  • additional information for all images of the messenger and device 100 may be generated.
  • the additional information may include at least one description data used to recommend a shared video, rather than parameters required for video playback.
  • the additional information has detailed data and, in some cases, may have shared related data.
  • Detailed data may include any one of image time data, location data, and object data.
  • the sharing related data may include history data that manages the sharing history of the video and keyword data that manages keywords used to select the shared video. Detailed data constituting additional information will be described in detail below.
  • Figure 5 is a flow chart regarding the generation and tagging of additional information for an image.
  • additional information may be generated to include metadata for each video (S205).
  • Metadata is a type of detailed data and may include at least one of video capture time data and capture location data. Metadata may be generated, for example, by settings of a messenger application.
  • the messenger application can generate metadata of the image of the user device 100 (hereinafter referred to as device image).
  • device images may be stored in a storage space named gallery of the user device 100. Additional information may include metadata for each device image.
  • the device image may be captured by the capturing unit 120 of the user device 100, or may be obtained from an external source other than the user device 100 through a messenger.
  • metadata may be generated by unique settings of the user device 100, extracted by a messenger application, and managed as detailed data of the video.
  • Metadata may be tagged in the video and managed in the video storage of the user device 100.
  • metadata may be managed in the storage area of the video, for example, a video list stored in the application.
  • the user device 100 may identify an object in the image and generate first object data (S210).
  • the video may include shared video, uploaded video, and device video.
  • the object data has information identifying at least one object in the image, and the identification information may be divided into first object data and second object data depending on the type.
  • the object data may include second object data along with first object data, depending on the sharing history of the image, which will be described later.
  • the object of the image may be a characteristic element in the image other than a simple background, and may be, for example, a person or an object other than a human.
  • the object may be, for example, a living creature, a unique artificial structure shown in an image, or a natural landscape.
  • the first object data may be managed so that a rough identifier that classifies each object included in the image is associated with the object.
  • Identification of objects used to generate rough identifiers can be realized using conventional image analysis techniques, such as object recognition techniques in images through machine learning. At least some processes of object recognition techniques based on machine learning can be implemented by applying a deep learning model.
  • Object recognition technologies to which deep learning models are applied may include the R-CNN (Region-Based Convolutional Neural Network) model group and the YOLO model group.
  • the R-CNN model family can be one of R-CNN, Fast R-CNN, and Faster R-CNN.
  • the YOLO model family can be one of YOLO, YOLOv2, and YOLOv3.
  • the video can be analyzed using an object recognition technique to identify each person.
  • a different rough identifier may be assigned to each identified person and associated with each person.
  • the rough identifier is not linked to personal information for each person, but may be composed of object indicators that indicate something different for each different object.
  • the user device 100 can check whether there is a video shared through the chat room among the videos stored in the video list of the messenger and the video storage of the user device 100 (S215).
  • the metadata and first object data generated in steps S205 and S210 constitute detailed data, and the detailed data can be tagged and managed as additional information of the video.
  • the user device 100 may generate history data for the shared video and generate second object data according to a predetermined condition (S220).
  • History data is data that manages the sharing history of a video, and in detail, may be data related to the sharing history of a video transmitted in at least one of the chat rooms in which the user participates.
  • Historical data may include, for example, chat room information, sharing time, sharing frequency, etc.
  • Chat room information may include, for example, data related to the user who sent the video, the participant who received the video, and all users who have participated in the shared chat room, when the chat room was opened, conversation activity in the chat room, etc.
  • the sharing frequency may include, for example, the number of shares for each chat room, the number of shares during a predetermined period, the total number of shares shared across all chat rooms, and the videos shared during a predetermined period.
  • the messenger application can check whether at least one of the profile data of the user participating in the chat room and the name data of the object related to the user matches the object recognized in the shared video.
  • the profile data and name data are substantially the same as those described in FIG. 2 .
  • second object data may be generated so that a detailed identifier from which at least one of profile data and name data is extracted is associated with the recognized object.
  • a series of processes for generating a detailed identifier may be performed by at least one of the user device 100 and the server 200.
  • the user device 100 can check whether a keyword related to the shared video exists (S225).
  • Keywords may be indexing elements associated with or used to select a video in a chat room where the video is shared. Keywords may be various types of elements, for example, text, image, voice, etc. When a video is shared in multiple chat rooms, keywords of the shared video can be detected from at least one of the multiple chat rooms.
  • keywords may have related keywords and query keywords.
  • the related keyword may be a keyword related to the selection of a shared video among conversation data exchanged between users of a chat room.
  • the messenger application can infer related keywords through machine learning on the correlation between conversation data and the selection of shared videos. For example, when content is transmitted/shared through conversations between users participating in a chat room and talking about topics related to a specific participant and his or her related people, a specific conversation is made to estimate the basis for selecting the shared content by learning the content of the conversation before sharing. Content can be detected by keyword.
  • keywords may include query keywords that include queries used by users to search shared videos.
  • the search can be performed by the user using a video search function provided in the message input window of the messenger (see 412 in FIG. 6).
  • the user can touch the video search key 416 provided in the message input window 412, and the messenger (or the user device 100) can convert the input window 412 into a video search field.
  • Video search The input window 412, which functions as a field, is not output as a message in the chat room 402 even if the user inputs text, but can present a recommended list of videos that match the input text.
  • the search may be performed by at least one of the search function provided by the video storage of the user device 100 linked to the messenger application and the search function using the messenger and other services during a conversation through a chat room. If the user actually shares the video finally selected through the search, the messenger application can detect the searched query as a keyword to select the shared video.
  • Query keywords may include not only queries entered by the user, but also extended queries inferred through machine learning based on the query.
  • the meta data and the first and second object data generated in steps S205 to S220 constitute detailed data, and the history data may be employed as shared related data.
  • Detailed data and shared related data can be tagged and managed as additional information of the video.
  • the user device 100 may generate the confirmed keyword as keyword data of the shared video (S230).
  • Keyword data can be generated based on related keywords and query keywords related to shared videos.
  • the detailed data and shared related data generated in steps S205 to S220 and S220 to S230 constitute additional information, and the additional information can be tagged in the image (S235).
  • Steps S205 to S220 are generated in the initial creation stage of the recommendation list, but after creation of the recommendation list, if sharing of a video through a messenger or uploading a video to the video list of the messenger is detected, steps S220 to S230 may be performed.
  • the user device 100 can automatically register the tagged video in the messenger's recommendation list (S110).
  • the user device 100 can register at least a shared video in a messenger and a video uploaded to the messenger in a recommendation list along with additional information.
  • the user device 100 may inquire the user via a messenger whether to register a device image tagged with additional information in the recommendation list. Depending on the user's additional response, the messenger can automatically register the tagged device video in the recommendation list. Additionally, the messenger can control the video selected by the user among the tagged device videos to be registered in the recommendation list. As another example, the messenger may ask the user whether to register the tagged device video in at least one of the messenger's video list and recommendation list. The messenger may register the device image in a list selected by the user.
  • the registration inquiry for the device image is performed in step S110, but as another example, the messenger may proceed with the registration inquiry to the user in step S105.
  • the user device 100 may detect whether a user's request to share a video occurred in a chat room in which the user participated (S115).
  • the sharing request can be realized in various forms. It can be detected whether a sharing request occurred from the user's selection of a recommendation-related menu or from a keyword entered into the message input window 412 that provides a video search function.
  • the recommendation-related menu may be, for example, a recommendation item (or recommendation menu; 428) or a search item provided as a sub-menu of the chat room 402, and is illustrated in FIGS. 6 to 8.
  • the menu is not limited to the embodiments illustrated in FIGS. 6 to 8 and may be provided in various ways.
  • Another example, that is, a sharing request by keyword is illustrated through FIGS. 9 to 11.
  • Figures 6 to 8 are diagrams showing an example of video recommendation implemented in a messenger.
  • FIG. 6 illustrates that multiple users Lee, Kim, Jung, and Ahn participate in a chat room 402 and exchange a conversation 406 on the topic of user Lee's daughter.
  • a situation is exemplified where users Lee and Kim exchanged a large amount of conversation 406 on the topic of their daughter and shared a video 404 of Lee's daughter during the conversation.
  • users Jung and Ahn later participate in the chat room 402, or even if they already participate, users Jung and Ahn do not participate in the conversation for a long time, so the already shared video 404 is , it may not be immediately confirmed on the current screen of the chat room 402 where Ahn started the conversation. Since many conversations cannot be displayed in full on the screen, users Jung and Ahn can check the conversations (406) and shared videos (404) that have already taken place between users Lee and Kim through the scroll function provided in the interface of the chat room (402). there is.
  • Figure 6 illustrates representative profile images 408a, 408b, and 408c that include images desired to be shown to other users to distinguish Kim, Jung, and Ahn from each other.
  • Jung's representative profile image 408b is registered using a face photo
  • Ahn's representative profile image 408c is registered using a photo of a natural landscape.
  • Kim's representative profile image 408a is illustrated as being registered as, for example, a graphic avatar provided by the application, a graphic character provided by another service, etc.
  • the representative profile images 408a, 408b, and 408c may be used as objects compared with the first and second object data of the image held by the user to be shared in the process of recommending the image to be shared.
  • the messenger application has a profile menu that manages the user's profile information, and the user can designate a representative profile video and register personal information and other images through the profile menu.
  • the user device 100 can identify objects in the registered profile image and other images through the menu.
  • the user device 100 may compare and analyze objects identified in the profile image and other images based on the first and second object data of the image stored in the recommendation list of the user requesting sharing. Object identification may be performed similarly to the method described in the first object data.
  • the user device 100 may extract a name related to an object identified in the image based on the comment.
  • Objects identified and names extracted from the video in the profile menu can be used as profile data and name data.
  • Lee plans to share his daughter's video by recognizing the situation of the conversation between Jung and Ahn, and enters the phrase 420 through the message input window 412 (hereinafter referred to interchangeably with input window) in the form of a message in the chat room 402. It can be displayed as .
  • the input window 412 can receive input from the user, in addition to text such as the phrase 420, as well as various emoticons and icons.
  • the video search key 416 provided in the input window 412 is an interface that receives a sharing request, and after touching the video search key 416, the user searches for the video to share through the input window 412. You can enter keywords or queries for this purpose. Sharing requests using the image search key 416 and input window 412 are illustrated in Figures 9 to 11.
  • the messenger application sequentially displays the tab 414 of the service menu, the entire album 424 provided as a sub-service of the service menu 422, and the recommendation menu 428. It can be activated with .
  • the user device 100 may recognize that a sharing request from user Lee has been received.
  • the full album 424 may manage images stored in at least one of the image list of the application and the image storage of the user device 100.
  • the chat room menu 410 can provide functions for managing various information and activities occurring in the chat room 402 and controlling them according to user requests.
  • the user device 100 may recommend a video with additional information that satisfies the recommendation criteria information of the chat room 402 among the videos in the recommendation list (S120).
  • the recommendation standard information may include at least one of sharing standard information according to predetermined conditions and context information of the chat room 402.
  • the sharing criteria information may be the sharing frequency required for the recommended video by the messenger or the current chat room 402 and an object identified from the video shared in the current chat room 402.
  • the sharing frequency may include at least one of the number of shares required for the video in at least one of the current and other chat rooms 402, a video shared during a specific period, and the number of shares required for the video during a predetermined period.
  • the identified object may be Lee's daughter's face extracted from a video 404 shared in a chat room 402.
  • Context information may be situational information derived from users and conversations in the chat room 402.
  • the context information may have at least one of user linkage information related to users who participated in the chat room 402 and conversation information extracted from conversation data of the chat room 402.
  • User linkage information may be information related to a user and other objects related to the user. Other objects may be, for example, the user, his or her family, a close friend, a companion animal, etc.
  • User linkage information can be obtained through each user's profile data and name data provided by the messenger application.
  • Profile data may include, for example, representative profile images 408a, 408b, and 408c and user images managed in the messenger.
  • Conversation information may be, for example, conversation topic words extracted from conversation data, characteristic objects in a conversation, expressions that estimate information, and situations, etc. Conversation information may be keywords extracted through machine learning on conversation data.
  • the recommendation standard information exemplifies sharing standard information related to the shared video 404 and context information extracted from the participants (Kim, Jung, Ahn, Lee) and the conversation 406.
  • the sharing standard information may be the face and sharing frequency of Lee's daughter identified from the shared video 404 in FIG. 7A.
  • Figure 6 illustrates that one video of Lee's daughter is shared, but when multiple videos have already been shared, the identification object of the sharing standard information is an object that commonly appears in the multiple shared videos (e.g., a face or other object).
  • the sharing frequency may further include the number of sharing required for commonly appearing objects.
  • the context information includes Jung's face, Officer Ahn, the profile data and name data of the participating users identified in the representative profile images 408a, 408b, and 408c in FIG. 7A, and the topic (Lee's daughter) extracted from the conversation 406. It may be characteristic information related to the daughter's name, etc.
  • the messenger application can search for images of additional information that meet recommendation standard information including information according to the above-described example from the recommendation list. Additionally, images through the recommendation menu 428 can be searched through various paths. For example, in addition to the recommendation list, the messenger can search for videos that meet recommendation criteria information from device videos and videos searched from external sites. To improve the efficiency of search processing and reduce resource burden, image search may be performed preferentially on images stored in the recommendation list of a messenger application, for example. If an image according to the recommendation criteria information is not found in the recommendation list, the device image stored in the user device 100 may be searched.
  • an image matching the recommendation standard information may be searched for by a search engine.
  • the search engine may be, for example, an engine provided by a search service linked to a messenger application.
  • at least one of shared criteria information and context information may be used as a search query.
  • Shared standard information provided through a search engine query may be, for example, an object image identified from a shared video and its characteristic information.
  • the context information provided through the query may be information related to the participants of the chat room 402 extracted from profile data and name data, conversation information extracted from the participants' conversations, etc.
  • Image search is not limited to the above-described embodiment and can be processed through various paths.
  • all images in the recommended list and images in the device 100 may be searched at the same time, and a search engine may be used as a secondary priority.
  • images can be searched using the three paths described above.
  • recommendation standard information may include Lee's daughter's face shown in the video 404 currently shared in the chat room 402 and the sharing frequency of existing shared videos.
  • the recommendation standard information includes profile data and name data of Jung's face, Officer Ahn, participants Kim, Jung, Ahn, and Lee, and conversations ( 406), it may be a conversation text related to Lee's daughter, etc.
  • the messenger application can preferentially search for additional information corresponding to the recommendation standard information through the recommendation list.
  • the corresponding additional information is additional information of the image managed in the recommendation list, and may be, for example, first and second object data, history data, related data, query data, etc.
  • the already shared video 404 can be managed in the recommendation list, but if no other video matching the recommendation criteria information exists in the recommendation list, the messenger application sequentially searches the video and the corresponding video through the device 100 and the search engine. You can search for additional information.
  • a video with additional information that meets the recommendation criteria information is selected as the recommended video 430, and as illustrated in FIG. 7B, a shared recommendation list including the recommended video 430 selected as a sharing candidate is provided to the device 100. can be displayed on the screen.
  • the shared recommendation list may be provided through the same or separate screen as the recommendation menu 428.
  • Figure 7b illustrates that the recommended video 430 is selected from among the videos in the recommendation list.
  • the recommended video (430) includes a video (404) already shared in the current chat room (402), another video of Lee's daughter related to the shared video (404) and conversation text, a video containing Jung related to the representative profile video (408b), etc. may be adopted to include.
  • the messenger application can check user Lee's response as to whether to select a video from the shared recommendation list (S125).
  • the messenger application can share the video selected by Lee in the chat room 402 and update additional information about the shared video (S130).
  • Lee can select the recommended video 430 through the selection tab at the top right of the recommended video 430 presented in the recommendation list.
  • Lee selects the video (432) related to his daughter to match the content of the conversation, and does not select the video (432) related to Jung.
  • a video 434 related to his daughter may be uploaded to be shared in the chat room.
  • This example shows all participants in the chat room 402 sharing the daughter-related video 442, but as another example, there is a closed sharing method in which the video is sent to only some of the participants (e.g., mentions, whispers, and chat room 402).
  • a video 432 related to the daughter may be shared through a secret chat room opened separately, etc.
  • additional information of the shared video 442 may be updated by a messenger application and managed by the user device 100.
  • the additional information updated may be historical data and related data of the shared video 442.
  • the messenger application sends the selected non-recommended video to the chat room (402) ), in addition to sharing, you can manage additional information of the shared video (S130).
  • additional information for the shared non-recommended video may be generated and tagged to the video. If additional information is already tagged in the shared non-recommended video, the additional information may be updated to reflect the sharing situation.
  • the above-described processing may refer to the management of additional information.
  • a video sharing request through a user's recommended menu is used as an example, but a sharing request through a menu can also be performed by a menu other than the recommended menu.
  • menus such as the video list managed by the application, recent items in FIG. 7B, download, and search may be activated, and recommendations based on sharing requests may begin.
  • the search menu may have an interface through which a user enters a search query to find an image to share.
  • the search query belongs to recommendation criteria information, and the recommendation criteria information can be created to include all of the search query, shared criteria information associated with the search query, and associated context information.
  • a messenger application can provide a video with additional information that meets recommendation criteria information related to a search query as a recommended video. When a user shares a recommended video, the messenger application can reflect the search query and context information related to the query, such as query data, related data, and history data of additional information.
  • Figure 9 is a diagram showing another example of video recommendation implemented in a messenger.
  • Figure 9 is an example of a sharing request using the image search function based on keywords provided in the input window 412, and shows a follow-up situation to Figure 6. In this respect, it is different from the embodiment of FIGS. 6 to 8 (particularly, FIGS. 7A and 7B) according to a sharing request according to menu selection.
  • the embodiment according to FIG. 9 is different from the embodiment of FIG. 6 in step S115 of FIG. 4.
  • the user for example, makes a touch input on the image search key (refer to 416 in FIG. 6) in the input window 412
  • the user device 100 can control the messenger so that the input window 412 functions as an image search field.
  • the image search key 416 can be changed to a text key 418.
  • the input window 412 can function as a text input interface by touching the text key 418.
  • Figure 9 illustrates that user Lee inputs a keyword 436 such as “my daughter Jane” into the input window 412 that functions as a video search field.
  • the user device 100 selects a video that satisfies the recommendation criteria information among the videos in the recommendation list as the recommended video 444 and creates a shared recommendation list 440. You can.
  • Recommendation standard information may be generated based on the input keyword 436, for example.
  • recommendation standard information may be generated based on shared standard information along with the input keyword 436.
  • the input keyword 436 may be analyzed by machine learning to derive extended keywords that are estimated to have identity and/or relevance to the input keyword.
  • the recommendation standard information according to the keyword 436 may include a phrase and an extended keyword of the keyword 436.
  • Recommendation standard information based on the keyword 436 includes, for example, in addition to the keyword phrase "My daughter Jane", extended keywords "Lee's daughter” and "7 years old” created by referring to conversation text related to Lee's daughter in the chat room 402. May include “daughter”, “daughter Jane”, etc.
  • the sharing standard information may be, for example, the face and sharing frequency of Lee's daughter identified from the shared video 404 in FIG. 6 .
  • the user device 100 may preferentially search for additional information corresponding to recommendation standard information through the recommendation list.
  • the additional information may be, for example, first and second object data, history data, related data, query data, etc.
  • a video with additional information that meets the recommendation criteria information is selected as the recommended video 440, and as illustrated in FIG. 9, a shared recommendation list 440 including the recommended video 440 is displayed in the input window 412 and Can be displayed on the same screen.
  • the recommended video 440 may include a video already shared in the current chat room 402 (404 in FIG. 6 ) and other videos of Lee's daughter.
  • Figure 9 illustrates that a recommended video is selected from among the videos in the recommendation list.
  • the user may select at least one recommended video as a shared video from the shared recommendation list 440 and touch the transmission key 438 to display the shared video in the chat room 402.
  • Figures 10 and 11 are diagrams showing another example of video recommendation implemented in a messenger.
  • Figures 10 and 11, like Figure 9, illustrate an example of a sharing request using the image search function by keyword provided in the input window 412.
  • the present disclosure illustrates a shared recommendation list 440 that includes recommended images selected from external content, such as device images and images from a search engine, in addition to the messenger's recommendation list.
  • the present disclosure differs from recommendations that rely only on images in the recommendation list illustrated in FIGS. 6 to 8.
  • Figure 10 illustrates that user Lee inputs a keyword 444 such as “AA neighborhood pub” into the input window 412 that functions as a video search field.
  • the user device 100 may select an image that satisfies recommendation criteria information among the images in the recommendation list, device images, and images from a search engine as the recommended image 448 and generate a shared recommendation list 446.
  • recommendation criteria information may be generated based on keywords 444, sharing criteria information, conversation data of the chat room 402, and content information.
  • Recommendation criteria information according to the keyword 444 may include a phrase and an extended keyword of the keyword 444.
  • Recommendation standard information according to the keyword 444 is, for example, the keyword phrase "Neighborhood AA Pub", as well as the extended keywords "Neighborhood AA” and "Neighborhood AA” generated by referring to the conversation text 420a related to the chat room 402. May include “bar in neighborhood”, “restaurant in neighborhood AA”, “attraction in neighborhood AA”, etc.
  • the sharing standard information may be, for example, the name of an object such as a pub or restaurant identified from an existing shared video and the sharing frequency.
  • the user device 100 may extract conversation information from conversation data 420a.
  • the conversation information may be, for example, a predetermined period of time before the current conversation date, a place such as a specific location AA, a characteristic environmental object related to the pub, a situation where a plurality of people are present, etc.
  • the user device 100 identifies the faces of Jung, Ahn, Kim, and Lee from the representative profile images 408a, 408b, and 408c, and in some cases, identifies the faces of each user based on the images, profile data, and name data held by each user. , each user's related parties can be identified.
  • Information related to identified participants, etc. may be user linkage information.
  • the user device 100 may generate recommendation standard information based on context information including conversation information and user linkage information.
  • the user device 100 may preferentially search for additional information corresponding to recommendation standard information through the recommendation list.
  • the additional information may be, for example, meta data, first and second object data, history data, related data, query data, etc.
  • Metadata may include, for example, at least one of shooting time data and shooting location data.
  • the first object data may be a rough identifier of an image related to a pub, a bar, etc.
  • the second object data may be a detailed identifier of an image related to Jung's profile data, for example.
  • related data includes conversation data of participants in the chat room 402 related to past video sharing
  • query data may include, for example, keywords used when searching for videos through the input window 412. .
  • additional information that meets the recommendation criteria information may be, for example, a few days ago, at least one of the participants in the chat room 402 gathered at a bar, pub, attraction, etc. located in AA in the neighborhood.
  • the user device 100 recommends images having additional information close to the recommendation standard information in the recommendation list, such as images taken by Jung at a local AA attraction with other participants and a plurality of images ( 448). This is illustrated by Album (Recommended) in Figure 11.
  • the user device 100 presents as a recommended video 448 a video with additional information that satisfies the recommendation standard information among the device videos, such as a video taken by Jung and other participants at a local AA pub and a plurality of videos. can do.
  • the device image is an image that is not included in the recommendation list, and may include additional information described with reference to FIG. 5, such as detailed data, first object data, etc. Additional information on the device image may be created in advance or may be created during the process of presenting a recommended image. Accordingly, the additional information of the device image in FIG. 11 may include a location such as neighborhood AA, shooting date, and a rough identifier of the image related to Jung, Pub, and bars.
  • the user device 100 searches for images matching the recommendation standard information through a search engine using the keywords 444 of the recommendation standard information and images, and presents the recommended video 448. You can.
  • the shared recommendation list 446 may be displayed as a recommended video 448 including videos from the recommendation list, device videos, and videos from a search engine.
  • the user device 100 may sequentially search for images in the recommendation list, device images, and images from a search engine according to predetermined conditions, and present only images that meet the recommendation criteria information as recommended images.
  • the user device 100 preferentially searches for images in the recommendation list, and if an image according to the recommendation criteria information is not found in the recommendation list, the user device 100 You can browse saved device images. Additionally, when a device image matching the recommendation standard information is not searched, the user device 100 may search for an image matching the recommendation standard information using a search engine using the above-described keywords 444, etc.
  • the user device 100 preferentially searches for images in the recommendation list, but since the images in the recommendation list that meet the recommendation criteria information are not searched, the user device 100 subsequently searches for images in the recommendation list. You can browse device images. If there is a device image that meets the recommendation criteria information, the user device 100, unlike FIG. 11, may not provide the image related to the recommendation list of the messenger as a recommended image, but may present only the device image as the recommended image 448. there is.
  • FIG. 12 is a flowchart of a method for adding external content to the video list of a messenger.
  • FIG. 13 is a diagram illustrating an additional inquiry about external content according to FIG. 12. The present disclosure is illustrated as being related to the situation in FIGS. 10 and 11.
  • FIGS. 10 and 11 when the user device 100 detects the input of a keyword 444 in the input window 412 functioning as an image search field (S305), it can recognize that there is a request to share the image. there is.
  • Figure 13 illustrates that user Lee inputs a keyword 444 such as “AA neighborhood pub” into the input window 412 that functions as a video search field.
  • the user device 100 may present an image that satisfies the recommendation criteria information among the images in the recommendation list, the device image, and the image from the search engine as the recommended image 448.
  • the recommended image 448 may include external content having at least one of a device image and data related to an image from a search engine (S310).
  • the series of processes for presenting a recommended video is substantially the same as the description of FIGS. 10 and 11.
  • the device image may be an image that is not included in the recommendation list, may already have additional information, or the additional information of the device image may be generated during the recommendation process.
  • Data related to an image by a search engine may include, for example, at least one of a content file and content link information.
  • the user device 100 may inquire whether to add the external content to the video list of the messenger (S315).
  • the user device 100 may display a selection tab 450 for a device video and a key (eg, “Add album”) related to addition to the video list.
  • “Add album” may be an interface for adding the device video selected through the selection tab 450 to the video list.
  • “Share” may be an interface for displaying the selected device video in the chat room 402.
  • “Add album” is located in the shared recommendation list 440, but the interface related to adding to the video list can be modified in various ways.
  • the user device 100 may add at least one of external content and link information of the content to the video list of the messenger (S320).
  • the device image can be added to the video list by touching “Add album.”
  • step S315 it may be inquired whether to add to at least one of the video list and the messenger's additional list.
  • an interface related to adding a video list eg, all albums in FIG. 7B or a video album managed in a messenger, etc.
  • adding a recommended list may be displayed.
  • keyword data including the keyword 444 entered in the input window 412 may be generated as additional information for the corresponding video.
  • videos that the user is likely to share in the future are managed in the messenger, the hassle of having to search for all videos in the messenger and the user device 100 in order to select a video suitable for sharing is eliminated. You can.
  • device videos, etc. can be managed in the messenger as much as possible, thereby increasing the usability of the messenger.
  • Exemplary methods of the present disclosure are expressed as a series of operations for clarity of explanation, but this is not intended to limit the order in which the steps are performed, and each step may be performed simultaneously or in a different order, if necessary.
  • other steps may be included in addition to the exemplified steps, some steps may be excluded and the remaining steps may be included, or some steps may be excluded and additional other steps may be included.
  • Computer-readable media may include program instructions, data files, data structures, etc., singly or in combination.
  • Program instructions recorded on the medium may be specially designed and configured for the present disclosure or may be known and usable by those skilled in the art of computer software.
  • Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks.
  • program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.
  • the hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present disclosure, and vice versa.
  • various embodiments of the present disclosure may be implemented by hardware, firmware, software, or a combination thereof.
  • one or more ASICs Application Specific Integrated Circuits
  • DSPs Digital Signal Processors
  • DSPDs Digital Signal Processing Devices
  • PLDs Programmable Logic Devices
  • FPGAs Field Programmable Gate Arrays
  • general purpose It can be implemented by a processor (general processor), controller, microcontroller, microprocessor, etc.
  • the scope of the present disclosure includes software or machine-executable instructions (e.g., operating systems, applications, firmware, programs, etc.) that allow operations according to the methods of various embodiments to be executed on a device or computer device, and such software. Or it includes a non-transitory computer-readable medium in which instructions, etc. are stored and can be executed on a device or computer.
  • software or machine-executable instructions e.g., operating systems, applications, firmware, programs, etc.

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Abstract

L'invention concerne un procédé pour la recommandation d'une image sur une messagerie, un support d'enregistrement et un dispositif informatique. Le procédé par lequel un dispositif informatique comprenant un processeur recommande une image sur une messagerie comprend les étapes consistant à : générer et étiqueter des informations supplémentaires concernant l'image, laquelle est gérée dans la messagerie ; enregistrer l'image étiquetée avec les informations supplémentaires dans une liste de recommandations de la messagerie ; recommander, en réponse à une requête de partage provenant d'un utilisateur ayant rejoint un salon de discussion, au moins une image enregistrée dans la liste de recommandations sur la base d'informations de référence de recommandation concernant le salon de discussion et les informations supplémentaires ; et partager, en réponse à une sélection de l'image recommandée par l'utilisateur, l'image sélectionnée dans le salon de discussion.
PCT/KR2023/010496 2022-10-24 2023-07-20 Procédé de recommandation d'image sur messagerie, support d'enregistrement et dispositif informatique WO2024090726A1 (fr)

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Citations (5)

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