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Friend recommendation method and device, equipment and storage medium

A friend recommendation and heterogeneous technology, which is applied in the fields of instrumentation, computing, electrical and digital data processing, etc., can solve the problems of inability to dig more in-depth spatial and temporal relationship information, insufficient representation ability of heterogeneous graph data, etc., and achieve the effect of improving accuracy.

Active Publication Date: 2022-06-03
SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the data representation ability of the heterogeneous graph in this method is insufficient, and it is impossible to dig deeper into the spatiotemporal relationship information.

Method used

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  • Friend recommendation method and device, equipment and storage medium
  • Friend recommendation method and device, equipment and storage medium
  • Friend recommendation method and device, equipment and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

Please refer to Figure 4-7 , Embodiment 1 of the present invention is a method for recommending friends based on a location social network, which aims to deeply model the complex connection relationship between different elements of the location social network so as to recommend possible friends for users in the real world.

[0044] This method is based on the heterogeneous multigraph. The difference between the heterogeneous multigraph and the traditional graph structure is mainly reflected in two aspects: 1) The types of nodes in the graph can be diversified. In this embodiment, there are two types of users and points of interest. node. 2) The types of connection relationships (edges) between nodes can be diversified. For example, there are multiple relationships between interest points and edges to represent different semantic relationships between them. Modeling a location social network through a structure such as a heterogeneous multigraph can make the entire data a who...

Embodiment 2

[0094] In an optional embodiment, the location social network data includes the user's friend relationship and historical access track and the location and category of the point of interest, and the historical access track includes the points of interest visited by the user and their corresponding access times , the node types in the socially heterogeneous multigraph include users and points of interest, and the edge types include friends, check-in, same-community, same-category, and co-occurrence;

[0095] In an optional embodiment, the input module 202 includes:

[0096] In an optional embodiment, the first output unit includes:

[0097] In an optional embodiment, the feature conversion unit is specifically configured to perform feature conversion on the weight vector of one side in the socially heterogeneous multigraph according to a feature conversion formula, to obtain the feature-transformed feature of the side. weight vector, the feature conversion formula is h e ’=σ(...

Embodiment 3

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Abstract

The invention discloses a friend recommendation method and device, equipment and a storage medium, and the method comprises the steps: obtaining location social network data, constructing a social heterogeneous multi-graph according to the location social network data, enabling nodes in the social heterogeneous multi-graph to comprise user nodes and interest point nodes, and enabling the user nodes and the interest point nodes to recommend friends when edges exist between the user nodes and the interest point nodes; an edge of at least one edge type exists between the two nodes; inputting the social heterogeneous multi-graph into a trained heterogeneous multi-graph neural network model, and outputting a final feature vector of each node; and respectively calculating the similarity between the final feature vector of each user node and the final feature vectors of other user nodes, and carrying out friend recommendation according to the similarity. According to the method, the complex connection relationship between different elements of the location social network can be well reflected, and the time-space relationship information in the location social network can be more deeply excavated, so that the recommendation accuracy can be improved.

Description

technical field [0001] The invention relates to the technical field of data mining, and in particular, to a friend recommendation method, device, device and storage medium. Background technique [0002] With the advancement of the times, network terminals such as mobile phones and computers have gradually entered everyone's life, and users' daily travel trajectories contain a large amount of points-of-interest (POI) information. A common life scenario is: several friends go to a restaurant for dinner, and leave comments about the restaurant on the Internet. Such information is often classified as location-based social networks (LBSN). The location social network not only reflects the user's historical access trajectory, but also reflects part of the user's social network, which hides very rich spatiotemporal information. Recommending friends that may exist in real life to users can not only help users expand their social circles, but also facilitate accurate advertising pu...

Claims

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Application Information

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IPC IPC(8): G06F16/9536G06F16/9535G06F16/9537
CPCG06F16/9536G06F16/9537G06F16/9535
Inventor 宋轩李永康范子沛尹渡邓锦亮
Owner SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA