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A Tag Recommendation Method Based on User Follow Relationship

A recommendation method, user's technology, applied in special data processing applications, machine learning, instrumentation, etc.

Active Publication Date: 2022-03-11
RENMIN UNIVERSITY OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, previous tag recommendation methods mainly focus on mining user-generated text data, but another information-rich data type in Weibo—following relationships among users—has not been properly mined and utilized.

Method used

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  • A Tag Recommendation Method Based on User Follow Relationship
  • A Tag Recommendation Method Based on User Follow Relationship
  • A Tag Recommendation Method Based on User Follow Relationship

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Embodiment Construction

[0026] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0027] The present invention will be further explained below in combination with specific embodiments.

[0028] The present invention provides a tag recommendation method based on user attention relationship, which specifically includes: 1) using the traditional PageRank algorithm to generate user influence scores and label influence scores 2) Use the graph embedding model to train the user attention network and user-label network to generate user vectors and label vector Combine the impact score Hash...

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Abstract

The present invention provides a label recommendation method based on user attention relationship. The method specifically includes: 1) using the traditional PageRank algorithm to generate user influence scores and label influence scores; -The label network is trained to generate user vectors and label vectors to recommend labels for users in combination with the influence score label influence score user vector and the label vector. The label recommendation method based on the user attention relationship provided by the present invention mines information from the user attention network and user label network that contain rich information, which can enrich the user characteristic information in the social network and enable service providers to better understand users .

Description

technical field [0001] The present invention relates to the technical field of label recommendation methods, in particular to a method for recommending labels to users based on the attention relationship among users in a social network by using graph embedding technology. Background technique [0002] In recent years, microblogging services like twitter and Sina Weibo have attracted a large number of users, and have formed a social network with a very large scale and influence. In order to better manage, organize, and understand these Weibo users, the task of automatically recommending tags for Weibo users has been proposed by the academic community. By automatically recommending tags to users, we can understand the hidden interests that users may have, and understand users' preferences and social relationships in more dimensions. However, previous tag recommendation methods mainly focus on mining user-generated text data, but another information-rich data type in Weibo—fol...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9536G06N20/00
CPCG06F16/9536G06N20/00
Inventor 赵鑫侯宇蓬陈俊华文继荣
Owner RENMIN UNIVERSITY OF CHINA
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