A personalized search method considering user-author relationship modeling

Abstract

The present invention discloses a personalized search method based on modeling considering user-author relation. The personalized search method comprises the following steps of (1) collecting a raw corpora from social networks to perform LDA model training to obtain a subject term matrix; (2) obtaining interestingness of a search user and followers thereof and mixed probability of a word set; (3) obtaining interaction rates of the followers on subjects; (4) obtaining similarity between interestingness of the search user on all subjects and an interestingness set of the followers on all subjects, and popularity of the followers; (5) obtaining evaluation models of the search user; (6) obtaining interaction rates of the search user and authors which are formed by the similarity and attention crossing rates; (7) obtaining an author evaluation index formed by influence, transmission capability, certification degree and authority; and (8) obtaining an evaluation index of the raw corpora which is formed by length ratio, external connection degree, tag value and retweet rate, thereby obtaining a search result. Text information and user-author relation information can be effectively utilized, and therefore the search result can be personalized.

Description

technical field [0001] The invention belongs to the field of individualized search, and in particular relates to an individualized search method for language models. Background technique [0002] As a broadcast social network platform that shares short and real-time information through the attention mechanism, Weibo and WeChat have become important channels for people to communicate. The explosive spread of content in social networks brings richer information to users, but also provides a lot of irrelevant and repetitive information. It is becoming more and more difficult to search for interesting information through social networks. [0003] Unlike traditional web content, social networking has its own characteristics. In terms of information content, the content in social networks is more focused on events and topics, the content is concise and rich, and covers a wide range of topics; There are huge differences in the relationship with searchers, and the characteristics ...

AI Technical Summary

Problems solved by technology

However, when modeling user interests, the key element of user-author relationship is not considered, and it is impossible to provide searchers with truly interested social network information from the perspective of searchers.

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