CN110719324A - Information pushing method and equipment - Google Patents
Information pushing method and equipment Download PDFInfo
- Publication number
- CN110719324A CN110719324A CN201910938994.4A CN201910938994A CN110719324A CN 110719324 A CN110719324 A CN 110719324A CN 201910938994 A CN201910938994 A CN 201910938994A CN 110719324 A CN110719324 A CN 110719324A
- Authority
- CN
- China
- Prior art keywords
- image
- user
- uploaded
- information
- target user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 79
- 238000004590 computer program Methods 0.000 claims description 9
- 241001465754 Metazoa Species 0.000 claims description 6
- 230000004044 response Effects 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 11
- 230000008569 process Effects 0.000 description 11
- 238000004891 communication Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 238000012549 training Methods 0.000 description 4
- 238000000605 extraction Methods 0.000 description 3
- 230000000644 propagated effect Effects 0.000 description 2
- 241000282326 Felis catus Species 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
-
- 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
- G06Q50/01—Social networking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Health & Medical Sciences (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Artificial Intelligence (AREA)
- Strategic Management (AREA)
- Primary Health Care (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Multimedia (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The embodiment of the disclosure discloses an information pushing method and equipment. One embodiment of the method comprises: the method comprises the steps of obtaining a first image uploaded by a first user, first position information associated with the first image, a second image uploaded by at least one second user and second position information associated with the second image, determining that the similarity between the uploaded second image and the first image meets a preset similarity condition from the at least one second user, taking the second user, the relation between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, as a target user, and pushing recommendation information associated with the target user to the first user.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to the technical field of internet, and particularly relates to an information push method and equipment.
Background
With the rapid development of the mobile internet, the social application provides convenience for communication of people, and people can add friends through a friend pushing function of the social application.
In the existing social platform, friend pushing is generally performed based on an address book, or social relationship analysis is performed through added friends and users who may have social relationships are recommended.
Disclosure of Invention
The embodiment of the disclosure provides an information pushing method and device.
In a first aspect, an embodiment of the present disclosure provides an information pushing method, which is applied to a server, and the method includes: acquiring a first image uploaded by a first user and first position information associated with the first image, and acquiring a second image uploaded by at least one second user and second position information associated with the second image; determining that the similarity between the uploaded second image and the first image meets a preset similar condition from at least one second user, and taking the second user, of which the relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, as a target user; and pushing recommendation information associated with the target user to the first user.
In a second aspect, an embodiment of the present disclosure provides an information pushing method, which is applied to a terminal, and the method includes: sending a first image and first position information associated with the first image to a server; and receiving recommendation information which is pushed by the server and is associated with the target user.
In a third aspect, an embodiment of the present disclosure provides an information pushing apparatus, applied to a server, where the apparatus includes: the device comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is configured to acquire a first image uploaded by a first user and first position information associated with the first image, and a second image uploaded by at least one second user and second position information associated with the second image; the confirming unit is configured to determine that the similarity between the uploaded second image and the first image meets a preset similar condition from at least one second user, and the second user, of which the relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, is used as a target user; the pushing unit is configured to push recommendation information associated with the target user to the first user.
In a fourth aspect, an embodiment of the present disclosure provides an information pushing method applied to a terminal, where the information pushing method includes: the sending unit is configured to send the first image and first position information associated with the first image to the server; the receiving unit is configured to receive recommendation information related to the target user and pushed by the server.
In a fifth aspect, an embodiment of the present disclosure provides an electronic device, including: one or more processors; a storage device having one or more programs stored thereon; when executed by one or more processors, cause the one or more processors to implement a method as described in any implementation of the first, second or third aspects.
In a sixth aspect, an embodiment of the present disclosure provides a computer-readable medium, on which a computer program is stored, which when executed by a processor implements the method as described in any of the implementations of the first and second aspects.
The information pushing method and the device server side provided by the embodiment of the disclosure obtain a first image uploaded by a first user, first position information associated with the first image, a second image uploaded by at least one second user, and second position information associated with the second image, then determine, from the at least one second user, that a similarity between the uploaded second image and the first image meets a preset similarity condition, and take the second user, as a target user, whose relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, and finally push recommendation information associated with the target user to the first user; according to the embodiment, the user who may arrive at the same place or shoot the same similar scenery or animal can be determined by analyzing the images uploaded by the user and the positions associated with the images, so that friend making recommendation is performed, and a friend making recommendation mode different from that in the prior art is provided.
Drawings
Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which some embodiments of the present disclosure may be applied;
FIG. 2 is a flow diagram of one embodiment of an information push method according to the present disclosure;
FIG. 3 is a schematic diagram of one application scenario for pushing recommendation information associated with a target user to a first user, according to an embodiment of the present disclosure;
FIG. 4 is a flow diagram of yet another embodiment of an information push method according to the present disclosure;
FIG. 5 is a flow diagram of another embodiment of an information push method according to the present disclosure;
fig. 6 is a flowchart of an embodiment of an information push method applied to a terminal according to the present disclosure;
FIG. 7 is a schematic block diagram of a computer system suitable for use with an electronic device to implement some embodiments of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates an exemplary architecture 100 to which the information push method of the present disclosure may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The terminal devices 101, 102, 103 interact with a server 105 via a network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as social platform software, a web browser application, a shopping application, an instant messaging tool, a mailbox client, and the like.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having a display screen and supporting the operation of social-type applications, including but not limited to smart phones, tablet computers, e-book readers, laptop portable computers, desktop computers, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server providing various services, such as a background server providing support for social-like applications running on the terminal devices 101, 102, 103. The background server may determine a target user meeting a preset condition from at least one second user of the social applications supported by the background server, and feed back recommendation information associated with the target user to the terminal device 101, 102, 103.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., software or software modules used to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The information push method provided in the embodiment of the present application may be executed by the terminals 101, 102, and 103, or may be executed by the server 105. Accordingly, the information pushing device may be disposed in the terminals 101, 102, 103, or may be disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to fig. 2, a flow 200 of one embodiment of an information push method according to the present disclosure is shown. The information pushing method is applied to a server and comprises the following steps:
step 201, a first image uploaded by a first user and first position information associated with the first image, and a second image uploaded by at least one second user and second position information associated with the second image are obtained.
In this embodiment, an executing subject of the information pushing method (for example, the server 105 shown in fig. 1) may obtain a first image uploaded by a terminal (for example, the terminal devices 101, 102, 103 shown in fig. 1) of a first user and first location information associated with the first image, and a second image uploaded by at least one second user and second location information associated with the second image. The first user may be a holding user of the terminal, or may be a login user of a social application installed on the terminal. The second user may be a logged-on user of the social-type application and a user who uploaded the image in a social space of the social-type application, such as the social-type application. The executing agent may obtain the second image uploaded by the at least one second user and the second location information associated with the second image from a local location (e.g., a database local to the server) or a remote location (e.g., a cloud database). The first image may be an image uploaded by the first user in the social space, and the first location information associated with the first image may represent a geographic location where the first user was when the first image was taken or a geographic location associated with image content of the first image. The second image may be an image uploaded by the at least one second user in the social space, and the second location information associated with the second image may represent a geographic location where the at least one second user was when the second image was taken or a geographic location associated with image content of the second image.
In some optional implementations of this embodiment, the first location information may include: the geographical position label generated when the first image is shot and/or the uploaded position information is related when the first user uploads the first image; the second location information includes: and the geographical position label generated when the second image is shot and/or the second user is associated with the uploaded position information when the second image is uploaded.
In this optional implementation, the first location information may be a geographic location tag carried by the first image, where the geographic location tag may be automatically added by a photographing apparatus used by the first user when photographing the first image. The first location information may also be a geographical location selected by the first user when uploading the first image. The execution subject may simultaneously acquire the geographic location tag generated when the first image is captured and the location information uploaded by the first user in association with uploading the first image, or may acquire only one of the geographic location tag and the location information as the first location information. The second location information may be a geographical location tag carried by the second image, where the geographical location tag may be automatically added by a photographing device used by the at least one second user when photographing the second image. The second location information may also be a geographical location selected by the at least one second user for uploading the second image. The execution subject may simultaneously acquire the geographic location tag generated when the second image is captured and the location information uploaded by the at least one second user in association with the first image when the first image is uploaded, or may acquire only one of the geographic location tag and the location information as the second location information. By the implementation mode, the acquisition modes of the position information associated with the image can be enriched, and the accuracy of acquiring the position information associated with the image is improved.
Step 202, determining, from at least one second user, that the similarity between the uploaded second image and the first image meets a preset similarity condition, and taking the second user, as a target user, where a relationship between second position information associated with the uploaded second image and the first position information meets a preset distance condition.
In this embodiment, the executing entity may find, as the target user, a second user, in the uploaded second image, whose similarity to the first image meets the preset similarity condition and whose relationship between the second location information associated with the uploaded second image and the first location information meets the preset distance condition, based on the at least one second user determined in step 201. Here, the preset similarity condition may be used to indicate a degree of similarity that needs to be satisfied between the first image and the second image uploaded by the target user, and for example, a similarity value between the second image and the first image may exceed a preset similarity threshold. The preset distance condition may be used to indicate a distance condition that needs to be satisfied between the second location indicated by the second location information uploaded by the target user and the first location indicated by the first location information, and for example, the distance between the second location and the first location may be within a preset distance range.
As an example, the executing entity may find, in a second image uploaded by at least one second user, a second image meeting a similarity condition by determining that a similarity value between a first image and the second image exceeds a preset similarity threshold value, eighty percent, to form a candidate second image set, determine, in the candidate second image set, the second image meeting the distance condition as a target image by determining whether a distance between a first position and a second position is within a range of 500 meters, which is the preset distance threshold value, and then take the second user corresponding to the target image as the target user.
Step 203, pushing recommendation information associated with the target user to the first user.
In this embodiment, after the execution subject determines the target user meeting the condition, the recommendation information associated with the target user is pushed to the first user. Here, the recommendation information may include information indicating some association relationship that may exist between the first user and the target user, and may include, for example, a reason for recommending the target user to the first user. Optionally, in response to determining that the first user allows sending recommendation information associated with the target user, the recommendation information associated with the target user is pushed to the first user.
In some optional implementations of this embodiment, pushing, to the first user, recommendation information associated with the target user includes: generating a target user information card containing a second image and second position information uploaded by a target user; and pushing the target user information card to the first user.
In this optional implementation manner, the execution subject may create a page related to the target user according to the second image uploaded by the target user and the second location information associated with the second image, and push the page related to the target user to the first user. For example, page content associated with the target user may be presented in a deck-like manner. Through the implementation mode, the recommendation information associated with the target user can be more intuitively and clearly presented to the first user.
In some optional implementations of this embodiment, the recommendation information associated with the target user may include: the contact information of the target user.
In this alternative implementation, the contact details of the target user may include at least one of the following: a telephone number, an account of a social application, an account of an instant messaging tool. Through the implementation mode, the first user can acquire the contact way of the target user and add the target user as a friend, so that a friend relationship is established with the target user.
In some optional implementation manners of this embodiment, the information pushing method may further include: and pushing recommendation information associated with the first user to the target user.
In this optional implementation manner, the execution subject may push recommendation information associated with the first user to the target user while determining the target user and pushing the recommendation information associated with the target user to the first user. Here, the recommendation information related to the first user may include the first image and the first location information. Optionally, in response to determining that the target user allows sending recommendation information associated with the first user, the recommendation information associated with the first user is pushed to the target user.
In some optional implementation manners of this embodiment, the step of acquiring the first image uploaded by the first user and the first location information associated with the first image, and the second image uploaded by the at least one second user and the second location information associated with the second image may include: in response to the operation that the first user issues the first image is detected, the first image uploaded by the first user and the first position information associated with the first image, and the second image uploaded by at least one second user and the second position information associated with the second image are obtained.
In this optional implementation manner, the execution main body may obtain, when detecting that the first user issues the first image, the first image issued by the first user and the first location information associated with the first image, determine, according to the first image issued by the first user and the first location information associated with the first image, a target user meeting a preset condition from among the at least one second user, and push recommendation information associated with the target user to the first user. Through the implementation mode, for example, after the first user publishes the first image in the social space, the recommendation information associated with the target object is pushed to the first user, and after the first user publishes the first image, the target user corresponding to the second image which has an association relation with the content of the first image is pushed to the first user to serve as the target user which the first user may be interested in, so that the success rate of the first user and the target user for establishing a friend relation is improved.
The information pushing method provided in the above embodiment of the present disclosure first obtains a first image uploaded by a first user, first location information associated with the first image, a second image uploaded by at least one second user, and second location information associated with the second image, then determines, from the at least one second user, that a similarity between the uploaded second image and the first image meets a preset similarity condition, and a second user whose relationship between the second location information associated with the uploaded second image and the first location information meets a preset distance condition is taken as a target user, and then pushes recommendation information associated with the target user to the first user, so as to push a target user corresponding to a second image having an association relationship with content of the first image to the first user according to the first image uploaded by the first user, thereby implementing targeted friend recommendation information push, the friend making efficiency is improved.
With continued reference to fig. 3, fig. 3 is a schematic diagram of one application scenario for pushing recommendation information associated with a target user to a first user, according to an embodiment of the present disclosure. In the application scenario of fig. 3, by way of example, a first user launches a social-like application using a first terminal, and publishes a first image taken by oneself in a social space and selects the geographical position of the oneself, wherein the first image is an image of a B building located in Beijing City, the first location information associated with the first image indicates a Beijing B building area, then the server determines that the uploaded second image contains a B building located in Beijing City and the second position information associated with the second image also indicates that the user A of the Beijing B building area is used as a target user in at least one second user, pushes recommendation information 301 associated with the user A to the first user, the recommendation information 301 may include a second image of a building B located in beijing city, which is taken by the user a, an account of the user a, and a recommendation for prompting the first user to add the user a as a friend.
With further reference to fig. 4, a flow 400 of yet another embodiment of an information push method is shown. The process 400 of the information pushing method, applied to the server, includes the following steps:
step 401, acquiring a first image uploaded by a first user and first location information associated with the first image, and acquiring a second image uploaded by at least one second user and second location information associated with the second image.
Step 401 is the same as step 201 in the foregoing embodiment, and the above description for step 201 also applies to step 401, which is not described herein again.
Step 402, determining, from at least one second user, that the uploaded second image and the first image contain the same object, and the second user whose distance between the first position indicated by the first position information and the second position indicated by the second position information is smaller than a first preset distance threshold is taken as a target user.
In this embodiment, the executing entity may find, based on the at least one second user determined in step 401, a second user, as a target user, where the uploaded second image and the first image contain the same object, and a distance between the first location indicated by the first location information and the second location indicated by the second location information is smaller than a first preset distance threshold. Specifically, the executing entity may identify, in a second image of at least one second user, a second image containing the same object as the first image through a trained image recognition model, to form a candidate second image set, determine, in the candidate second image set, a target image meeting a distance condition by determining whether a distance between the first position and the second position is smaller than a first preset distance threshold, and take the second user corresponding to the target object as the target user. In the training process of the image recognition model, the target objects of each category contained in the sample images in the training sample set are labeled, so that the trained image recognition model can recognize the target objects of each category.
In some optional implementations of the present embodiment, determining the second image whose similarity to the first image meets the preset similarity condition includes: acquiring appearance information of a first scene object in a first image; and identifying a second image containing a second scene object matched with the appearance information from second images uploaded by at least one second user as a second image containing the same object as the first image.
In this alternative implementation, the first image and the second image may be images containing scene objects. The execution subject may identify, from the second image uploaded by the at least one second user, a second image containing a second scene object matching the appearance information as a second image containing the same object as the first image, by identifying appearance information of the first scene object in the first image, and based on the appearance information. Here, the appearance information of the first scene object may be an outline, a color, and other appearance features of the first scene object, and may be extracted using a trained scene appearance information extraction model. In the training process of the landscape appearance information extraction model, the image containing the scenery object is selected as the sample image, the appearance information of the scenery object contained in the sample image is labeled, and the appearance characteristics such as the outline, the color and the like of the scenery object can be labeled, so that the trained landscape appearance information extraction model can extract the appearance information such as the outline, the color and the like of the scenery object. As an example, the first scene object included in the first image may be a people hall building located in beijing city, the execution subject identifies a second image including the second scene object and the second scene object being the people hall building located in beijing city from at least one second image according to appearance information of the people hall building located in beijing city, and takes a second user corresponding to the second image including the second scene object of the people hall building located in beijing city as a target user.
The realization mode matches the second image containing the same scenery object by taking the appearance information of the first scenery object contained in the first image as the basis, and matches by taking the appearance information of the first scenery object as the overall characteristic of the first image, so that the second image containing the same scenery object can be quickly determined.
In some optional implementations of the embodiment, the obtaining appearance information of the first scene object in the first image includes: extracting image features of a first scene object in a first image; and if the image characteristics are matched with the scene objects in the preset scene object library, taking the appearance information of the matched scene objects as the appearance information of the first scene object.
In this optional implementation manner, after the image feature of the first scene object of the first image is extracted, the execution subject may search, according to the image feature of the first scene object, the image feature of the matched scene object in the preset scene object library, and use appearance information of the image feature of the matched scene object as appearance information of the first scene object. Here, the preset scene object library may include image features of pre-stored famous scene objects, such as a church of the paris holy house, an eiffel tower, an eastern mingbeads tv tower, and the like. The landscape image can carry the geographical position label of the famous scenery object, so that in the process that the execution main body determines the image characteristics of the scenery object matched with the image characteristics of the first scenery object from the preset scenery object library, the distance between the first position indicated by the first position information and the geographical position represented by the geographical position label carried by the scenery image is within the preset distance threshold range, the image characteristics matched with the scenery object more accurately and more quickly are realized, and the appearance characteristics of the scenery object are used as the appearance characteristics of the first landscape object.
The appearance information of the high-definition full-view landscape object provided by the preset scenery object library in the implementation mode is used as the appearance information of the first scenery object in the first image, so that the appearance information of the first scenery object can be presented more comprehensively and more accurately, and the matching accuracy of the first image and the second image is improved.
Step 403, pushing the first recommendation information to the first user.
In this embodiment, after the executive owner determines the target user meeting the condition, first recommendation information associated with the target user may be pushed to the first user, where the first recommendation information may include information for prompting the target user to visit the same geographical location as the first user. Here, the first recommendation information may include the second image uploaded by the target user, the second location information, and a recommendation reason. As an example, the reason for the recommendation may be "he/she has gone the same place as you", "he/she has shot the same scene in the same place as you". Therefore, the success rate of adding the target user to be the friend by the first user can be improved.
As can be seen from fig. 4, in the process 400 of the information pushing method in this embodiment, it is determined from at least one second user that the uploaded second image and the first image contain the same object, and the second user whose first position indicated by the first position information and second position indicated by the second position information are smaller than the first preset distance threshold is taken as a target user, so that the target user is found out in a targeted manner and quickly, and meanwhile, the success rate of creating a friend relationship between the first user and the target user can be improved based on the recommendation reason that the first user and the target user have shot the same scene object within the preset distance range.
With further reference to fig. 5, a flow 500 of another embodiment of an information push method is shown. The process 500 of the information pushing method, applied to the server, includes the following steps:
Step 501 is the same as step 201 in the foregoing embodiment, and the above description for step 201 also applies to step 501, which is not described herein again.
In this embodiment, the executing entity may find, based on the at least one second user determined in step 501, a second user, as a target user, where the uploaded second image and the first image include similar objects or the second image and the first image are similar as a whole, and a distance between the first location indicated by the first location information and the second location indicated by the second location information exceeds a second preset distance threshold.
In some optional implementations of this embodiment, the determining the second image containing the similar object to the first image includes: extracting image features of a first primary object of interest in the first image, the first primary object of interest comprising a scene object or an animal object located in a central region of the first image; and identifying a second image containing a second main object of interest matched with the image characteristics from the second image uploaded by at least one second user as a second image containing similar objects with the first image, wherein the second main object of interest comprises a scene object or an animal object positioned in the central area of the second image.
In this alternative implementation, the executing entity may first locate a central region of the image, use an object in the central region as a first main object of interest, recognize an image feature of the first main object of interest through a trained target object detection model, and recognize a second image, which contains a second main object of interest and is matched with the image feature, from a second image uploaded by at least one second user, as a second image containing a similar object to the first image. The first main object of interest may be an object occupying an area in a central area of the first image exceeding a preset area ratio. The second main object of interest may be an object occupying an area in a central area of the second image exceeding a preset area ratio. By way of example, the primary object of interest here may be an animal, a building, an item, etc. Specifically, in the training process of the target object detection model, the object in the central region of the sample image is labeled, so that the trained target object detection model can quickly identify the image features of the main object in the central region of the image.
According to the implementation method, the second image containing the similar object is determined according to the image characteristics of the main attention object contained in the first image, and the target object which is commonly interested between the first user and the target user can be determined more accurately according to the similarity degree of the main object in the central area of the image as the basis of the similarity degree between the images.
In some optional implementations of this embodiment, the determining the second image that is entirely similar to the first image includes: extracting integral image features of the first image; and identifying a second image which is matched with the overall image characteristics from the second images uploaded by at least one second user as a second image which is overall similar to the first image.
In this optional implementation, when it is required to determine a second image that is entirely similar to the first image, the executing entity may identify, after extracting the overall image feature of the first image, a second image that matches the overall image feature from among second images uploaded by at least one second user, as the second image that is entirely similar to the first image. Here, the condition that the two images are entirely similar may include: the two images are not identical, but the similarity between the global features of the two images exceeds a certain threshold. On this basis, optionally, the condition that the two images are similar as a whole may further include: the difference between the local features of the two images exceeds a certain range. The global feature may include features such as an overall composition layout of the image, a hue and a style of the image, in practice, it may be determined whether the above-mentioned overall similarity condition is satisfied between the first image and the second image, for example, when a similarity between the global features of the first image and the second image exceeds a certain threshold, but a difference between local features of the first image and the second image also exceeds a certain range, it may be determined that the first image is entirely similar to the second image.
The implementation mode determines the second image with the overall similar first image based on the overall image characteristics of the first image, and more comprehensively considers the association relationship of the overall characteristics among the images.
In this embodiment, after the executive owner determines the target user meeting the condition, second recommendation information associated with the target user may be pushed to the first user, where the second recommendation information may include information for prompting that the content of the first image is associated with the content of the second image. Here, the second recommendation information may include the second image uploaded by the target user, the second location information, and a recommendation reason. As an example, the reason for the recommendation may be "he/she and you have similar pets", "he/she and you have cats of the same breed". Therefore, the success rate of adding the target user to be the friend by the first user can be improved.
As can be seen from fig. 5, in the information pushing method in this embodiment, the process 500 determines, from at least one second user, that the uploaded second image and the first image include similar objects or that the second image is integrally similar to the first image, and the second user whose first position indicated by the first position information and second position indicated by the second position information exceed the second preset distance threshold is used as a target user, so as to achieve targeted and fast finding of the target user, and improve a success rate of establishing a friend relationship between the first user and the target friend based on common interests between the first user and the target user, for example, that both users enjoy the same type of pets or both users enjoy the same type of natural landscapes.
With further reference to fig. 6, a flow chart 600 of one embodiment of an information push method applied to a terminal is shown. The process 600 of the information pushing method includes the following steps:
In this embodiment, an executing body of the information pushing method (such as the terminals 101, 102, 103 shown in fig. 1) may send the first image and the first location information associated with the first image to a server (such as the server 105 shown in fig. 1).
Here, the server may be configured to: acquiring a first image uploaded by a first user and first position information associated with the first image, and acquiring a second image uploaded by at least one second user and second position information associated with the second image; determining that the similarity between the uploaded second image and the first image meets a preset similar condition from at least one second user, and taking the second user, of which the relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, as a target user; and pushing recommendation information associated with the target user to the first user.
In this embodiment, the execution main body may receive recommendation information related to a target user, where the target user is a second user whose similarity between an uploaded second image and a first image determined by the server from at least one second user meets a preset similarity condition, and a relationship between second location information related to the uploaded second image and the first location information meets a preset distance condition.
In some optional implementations of the embodiment, the preset similar condition includes that the second image and the first image contain the same object; the preset distance condition includes that the distance between the first position indicated by the first position information and the second position indicated by the second position information is smaller than a first preset distance threshold, and the receiving of the recommendation information related to the target user and pushed by the server includes: and receiving first recommendation information pushed by a server.
In this optional implementation manner, when the server sets the similar condition that the second image and the first image contain the same object and the preset distance condition includes that the distance between the first location indicated by the first location information and the second location indicated by the second location information is smaller than the first preset distance threshold, the execution main body may receive recommendation information associated with a target user selected by the server from the at least one second user based on the preset condition, where the recommendation information includes information for prompting the target user to visit the same geographical location as the first user who sent the first image. By the implementation mode, the success rate of the friend relationship between the first user and the target user is improved based on the recommendation reason that the first user and the target user shoot the same scene object within the preset distance range.
In some optional implementations of the embodiment, the preset similar condition includes that the second image and the first image contain similar objects or that the second image and the first image are similar as a whole; the preset distance condition includes that a distance between the first position indicated by the first position information and the second position indicated by the second position information exceeds a second preset distance threshold. The receiving of the recommendation information related to the target user pushed by the server includes: and receiving second recommendation information pushed by the server.
In this optional implementation manner, when the server sets the similar condition that the second image and the first image contain the same object and the preset distance condition includes that the distance between the first location indicated by the first location information and the second location indicated by the second location information is smaller than the first preset distance threshold, the execution main body may receive recommendation information associated with a target user selected by the server from the at least one second user based on the preset condition, where the recommendation information includes information for prompting that the content of the first image is associated with the content of the second image. Through the implementation mode, the success rate of establishing the friend relationship between the first user and the target user can be improved based on the common interests and hobbies possibly existing between the first user and the target user, for example, both the first user and the target user like pets of the same type or both the first user and the target user like natural landscapes of the same type.
In some optional implementations of this embodiment, the first location information includes: the geographical position label generated when the first image is shot and/or the uploaded position information is related when the first user uploads the first image; the second location information includes: and the geographical position label generated when the second image is shot and/or the second user is associated with the uploaded position information when the second image is uploaded.
In this optional implementation, the first location information may be a geographic location tag carried by the first image, where the geographic location tag may be automatically added by a photographing apparatus used by the first user when photographing the first image. The first location information may also be a geographical location selected by the first user when uploading the first image. The execution subject may simultaneously acquire the geographic location tag generated when the first image is captured and the location information uploaded by the first user in association with uploading the first image, or may acquire only one of the geographic location tag and the location information as the first location information. The second location information may be a geographical location tag carried by the second image, where the geographical location tag may be automatically added by a photographing device used by the at least one second user when photographing the second image. The second location information may also be a geographical location selected by the at least one second user for uploading the second image. The execution subject may simultaneously acquire the geographic location tag generated when the second image is captured and the location information uploaded by the at least one second user in association with the first image when the first image is uploaded, or may acquire only one of the geographic location tag and the location information as the second location information. By the implementation mode, the mode of acquiring the position information associated with the image can be enriched, and the accuracy of acquiring the position information associated with the image is improved.
In some optional implementations of this embodiment, the recommendation information associated with the target user includes: the contact information of the target user.
In this alternative implementation, the contact details of the target user may include at least one of the following: a telephone number, an account of a social application, an account of an instant messaging tool. Through the implementation mode, the first user can acquire the contact way of the target user and add the target user as a friend, so that a friend relationship is established with the target user.
In some optional implementation manners of this embodiment, sending, to the server, the first image and the first location information associated with the first image includes: and in response to the detection of the operation of the first user for issuing the first image, sending the first image and the first position information associated with the first image to the server.
In this implementation manner, in this optional implementation manner, the execution subject may send the first image and the first location information associated with the first image to the server when detecting that the first user issues an operation of the first image. By the implementation method, the recommendation information associated with the target object can be pushed to the first user when the first user publishes the first image in the social space, the target user corresponding to the second image which has an association relation with the content of the first image is pushed to the first user when the first user publishes the first image, and the success rate of the first user and the target user for establishing a friend relation is improved.
In some optional implementation manners of this embodiment, the receiving recommendation information related to the target user pushed by the server includes: and receiving a target user information card which is sent by the server and contains the second image and the second position information uploaded by the target user.
In this optional implementation manner, the execution subject may receive a page related to the target user, which is pushed by the server and created according to the second image uploaded by the target user and the second location information associated with the second image. Through the implementation mode, the recommendation information associated with the target user can be more intuitively and clearly presented to the first user.
According to the information push method provided by the embodiment, the first image and the first position information associated with the first image are sent to the server, and the recommendation information associated with the target user and pushed by the server is received, so that the target user can be selected in a targeted manner according to the first image and the first position information associated with the first image to push to the first user, and the friend making efficiency is improved.
As shown in fig. 7, electronic device 700 may include a processing means (e.g., central processing unit, graphics processor, etc.) 701 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from storage 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the electronic apparatus 700 are also stored. The processing device 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Generally, the following devices may be connected to the I/O interface 705: input devices 706 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 707 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 708 including, for example, magnetic tape, hard disk, etc.; and a communication device 709. The communication means 709 may allow the electronic device 700 to communicate wirelessly or by wire with other devices to exchange data. While fig. 7 illustrates an electronic device 700 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 7 may represent one device or may represent multiple devices as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication means 709, or may be installed from the storage means 708, or may be installed from the ROM 702. The computer program, when executed by the processing device 701, performs the above-described functions defined in the methods of embodiments of the present disclosure.
It should be noted that the computer readable medium of the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a first image uploaded by a first user and first position information associated with the first image, and acquiring a second image uploaded by at least one second user and second position information associated with the second image; determining that the similarity between the uploaded second image and the first image meets a preset similar condition from at least one second user, and taking the second user, of which the relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, as a target user; pushing a recommendation letter associated with a target user to a first user; or sending the first image and the first position information associated with the first image to the server; receiving recommendation information related to a target user and pushed by a server, wherein the server is configured to: acquiring a first image uploaded by a first user and first position information associated with the first image, and acquiring a second image uploaded by at least one second user and second position information associated with the second image; determining that the similarity between the uploaded second image and the first image meets a preset similar condition from at least one second user, and taking the second user, of which the relationship between the second position information associated with the uploaded second image and the first position information meets a preset distance condition, as a target user; and pushing recommendation information associated with the target user to the first user.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (25)
1. An information pushing method is applied to a server and comprises the following steps:
acquiring a first image uploaded by a first user and first position information associated with the first image, and acquiring a second image uploaded by at least one second user and second position information associated with the second image;
determining, from the at least one second user, that the similarity between the uploaded second image and the first image meets a preset similarity condition, and taking a second user, as a target user, where a relationship between second location information associated with the uploaded second image and the first location information meets a preset distance condition;
and pushing recommendation information associated with the target user to the first user.
2. The method according to claim 1, wherein the preset similar condition comprises that the second image and the first image contain the same object; the preset distance condition comprises that the distance between the first position indicated by the first position information and the second position indicated by the second position information is smaller than a first preset distance threshold value.
3. The method according to claim 2, wherein determining a second image whose similarity to the first image meets a preset similarity condition comprises:
acquiring appearance information of a first scene object in the first image;
and identifying a second image containing a second scene object matched with the appearance information from the second images uploaded by the at least one second user as a second image containing the same object as the first image.
4. The method of claim 3, wherein said obtaining appearance information of a first scene object in said first image comprises:
extracting image features of a first scene object in the first image;
and if the image characteristics are matched with the scenery objects in the preset scenery object library, taking the appearance information of the matched scenery objects as the appearance information of the first scenery objects.
5. The method of claim 2, wherein the pushing recommendation information associated with the target user to the first user comprises:
and pushing first recommendation information to the first user, wherein the first recommendation information comprises information for prompting the target user and the first user to visit the same geographical position.
6. The method according to claim 1, wherein the preset similarity condition comprises that the second image and the first image contain similar objects or that the second image and the first image are similar as a whole; the preset distance condition includes that a distance between a first position indicated by the first position information and a second position indicated by the second position information exceeds a second preset distance threshold.
7. The method according to claim 6, wherein the preset similarity condition comprises that the second image and the first image contain similar objects, and determining the second image with the similarity meeting the preset similarity condition with the first image comprises:
extracting image features of a first primary object of interest in the first image, the first primary object of interest comprising a scene object or an animal object located in a central region of the first image;
and identifying a second image containing a second main object of interest and matched with the image characteristics from the second image uploaded by the at least one second user as a second image containing similar objects with the first image, wherein the second main object of interest comprises a scene object or an animal object in the central area of the second image.
8. The method according to claim 6, wherein the preset similarity condition comprises that the second image is similar to the first image in whole, and determining the second image with the similarity degree to the first image meeting the preset similarity condition comprises:
extracting integral image features of the first image;
and identifying a second image which is matched with the overall image characteristic from the second images uploaded by the at least one second user as a second image which is overall similar to the first image.
9. The method of claim 6, wherein the pushing recommendation information associated with the target user to the first user comprises:
second recommendation information is pushed to the first user, and the second recommendation information comprises information used for prompting that the content of the first image is associated with the content of the second image.
10. The method of claim 1, wherein the first location information comprises: the geographical position label generated when the first image is shot and/or the first user are associated with uploaded position information when the first image is uploaded; the second location information includes: and the geographical position label generated when the second image is shot and/or the second user is associated with the uploaded position information when the second image is uploaded.
11. The method of any of claims 1-10, wherein the recommendation information associated with the target user includes: the contact information of the target user.
12. The method of claim 1, wherein the obtaining a first image uploaded by a first user and first location information associated with the first image, a second image uploaded by at least one second user and second location information associated with the second image comprises:
in response to the operation that the first user issues the first image is detected, a first image uploaded by the first user and first position information associated with the first image, and a second image uploaded by at least one second user and second position information associated with the second image are obtained.
13. The method of claim 1, wherein the pushing recommendation information associated with the target user to the first user comprises:
generating a target user information card containing the second image uploaded by the target user and the second position information;
and pushing the target user information card to the first user.
14. The method of claim 1, wherein the method further comprises:
and pushing recommendation information associated with the first user to the target user.
15. An information push method is applied to a terminal and comprises the following steps:
sending a first image and first position information associated with the first image to a server;
receiving recommendation information related to a target user and pushed by a server, wherein the target user is a second user of which the similarity between an uploaded second image and the first image determined by the server from at least one second user meets a preset similarity condition and the relationship between second position information related to the uploaded second image and the first position information meets a preset distance condition.
16. The method of claim 15, wherein the preset similarity condition comprises that the second image and the first image contain the same object; the preset distance condition comprises that the distance between the first position indicated by the first position information and the second position indicated by the second position information is smaller than a first preset distance threshold value.
17. The method of claim 16, wherein the receiving recommendation information associated with the target user pushed by the server comprises:
and receiving first recommendation information pushed by a server, wherein the first recommendation information comprises information used for prompting the target user and a first user sending the first image to visit the same geographical position.
18. The method according to claim 15, wherein the preset similarity condition comprises that the second image and the first image contain similar objects or that the second image and the first image are similar as a whole; the preset distance condition includes that a distance between a first position indicated by the first position information and a second position indicated by the second position information exceeds a second preset distance threshold.
19. The method of claim 18, wherein the receiving recommendation information associated with the target user pushed by the server comprises:
and receiving second recommendation information pushed by a server, wherein the second recommendation information comprises information used for prompting that the content of the first image is associated with the content of the second image.
20. The method of claim 15, wherein the first location information comprises: the geographical position label generated when the first image is shot and/or the first user are associated with uploaded position information when the first image is uploaded; the second location information includes: and the geographical position label generated when the second image is shot and/or the second user is associated with the uploaded position information when the second image is uploaded.
21. The method of any of claims 15-20, wherein the recommendation information associated with the target user comprises: the contact information of the target user.
22. The method of claim 15, wherein the sending the first image and the first location information associated with the first image to the server comprises:
and responding to the operation that the first user issues the first image, and sending the first image and first position information associated with the first image to a server.
23. The method of claim 15, wherein the receiving recommendation information associated with the target user pushed by the server comprises:
and receiving a target user information card which is sent by a server and contains the second image uploaded by the target user and the second position information.
24. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-23.
25. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method of any one of claims 1-23.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910938994.4A CN110719324A (en) | 2019-09-30 | 2019-09-30 | Information pushing method and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910938994.4A CN110719324A (en) | 2019-09-30 | 2019-09-30 | Information pushing method and equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110719324A true CN110719324A (en) | 2020-01-21 |
Family
ID=69211254
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910938994.4A Pending CN110719324A (en) | 2019-09-30 | 2019-09-30 | Information pushing method and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110719324A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111291337A (en) * | 2020-02-17 | 2020-06-16 | 腾讯科技（深圳）有限公司 | Method, device and storage medium for creating incidence relation |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105897570A (en) * | 2016-06-29 | 2016-08-24 | 北京小米移动软件有限公司 | Pushing method and device |
| US20160248863A1 (en) * | 2011-08-04 | 2016-08-25 | Facebook, Inc. | Recommendations Based On Geolocation |
| CN106504104A (en) * | 2016-10-27 | 2017-03-15 | 江西瓷肌电子商务有限公司 | A kind of method of social activity of being made friends based on face recognition |
| CN106528709A (en) * | 2016-10-26 | 2017-03-22 | 北京小米移动软件有限公司 | Social information recommendation method and apparatus |
| CN106980688A (en) * | 2017-03-31 | 2017-07-25 | 上海掌门科技有限公司 | A kind of method, equipment and system for being used to provide friend-making object |
-
2019
- 2019-09-30 CN CN201910938994.4A patent/CN110719324A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160248863A1 (en) * | 2011-08-04 | 2016-08-25 | Facebook, Inc. | Recommendations Based On Geolocation |
| CN105897570A (en) * | 2016-06-29 | 2016-08-24 | 北京小米移动软件有限公司 | Pushing method and device |
| CN106528709A (en) * | 2016-10-26 | 2017-03-22 | 北京小米移动软件有限公司 | Social information recommendation method and apparatus |
| CN106504104A (en) * | 2016-10-27 | 2017-03-15 | 江西瓷肌电子商务有限公司 | A kind of method of social activity of being made friends based on face recognition |
| CN106980688A (en) * | 2017-03-31 | 2017-07-25 | 上海掌门科技有限公司 | A kind of method, equipment and system for being used to provide friend-making object |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111291337A (en) * | 2020-02-17 | 2020-06-16 | 腾讯科技（深圳）有限公司 | Method, device and storage medium for creating incidence relation |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6784308B2 (en) | Programs that update facility characteristics, programs that profile facilities, computer systems, and how to update facility characteristics | |
| CN108268573B (en) | Method and device for pushing information | |
| EP2851811B1 (en) | Method and device for achieving augmented reality application | |
| CN107426328B (en) | Information pushing method and device | |
| US9832614B2 (en) | Method, server and terminal for information interaction | |
| US10380748B2 (en) | Method and apparatus for determining to-be-superimposed area of image, superimposing image and presenting picture | |
| CN110677267B (en) | Information processing method and device | |
| US10614621B2 (en) | Method and apparatus for presenting information | |
| CN107172209B (en) | Information pushing method and device | |
| US20200394700A1 (en) | Forecasting Expenditures to Improve Customer Shopping Experience in Store Environment | |
| JP2016525236A (en) | Method, apparatus, and system for screening augmented reality content | |
| CN111787042B (en) | Method and device for pushing information | |
| CN112218027A (en) | Information interaction method, first terminal device, server and second terminal device | |
| CN106549860B (en) | Information acquisition method and device | |
| CN111475722B (en) | Method and apparatus for transmitting information | |
| CN112148962B (en) | Method and device for pushing information | |
| CN110719324A (en) | Information pushing method and equipment | |
| CN109947526B (en) | Method and apparatus for outputting information | |
| CN113628097A (en) | Image special effect configuration method, image recognition method, image special effect configuration device and electronic equipment | |
| CN108898416B (en) | Method and apparatus for generating information | |
| CN110968769A (en) | Method and equipment for pushing information and displaying information | |
| CN112307324B (en) | Information processing method, device, equipment and medium | |
| CN110188833B (en) | Method and apparatus for training a model | |
| CN112153091B (en) | Method and device for determining relevance of equipment | |
| CN111897951A (en) | Method and apparatus for generating information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200121 |
|
| RJ01 | Rejection of invention patent application after publication |