Inference method and device of MicroBlog user interests

Abstract

The invention provides a method for establishing a MicroBlog user interest inference model. The method comprises an interest label calculation model, an interest model used for MicroBlog text content extraction and a blogger interest point model used for blogger social relationship extraction, and the three models are fused through a model fusion strategy to obtain the final MicroBlog user interest inference model. The method combines personal information, MicroBlog contents and the social relationship, adopts a USER strategy that all MicroBlog contents of the same blogger are mixed by aiming at the sparsity problem of the MicroBlog contents, mines an implicit theme of the MicroBlog by a LPA (Label propagation algorithm), puts forwards a social label propagation algorithm on the basis of a network formed by blogger attention, and calculates influence on the blogger by various interest labels. The method exhibits good identification capability and information filtering capability, and filters false information to identify false bloggers before recommendation is carried out, so that the recommendation quality and accuracy of a recommendation system can be improved, and better experience is brought for the blogger.

Description

technical field [0001] The invention belongs to the technical field of Internet communication, and in particular relates to a method and a device for establishing a microblog user interest reasoning model. Background technique [0002] With the popularization of Weibo, various applications based on Weibo have also emerged. Among them, the personalized recommendation technology for bloggers has received a lot of attention, and academic research on personalized recommendation of Weibo has also begun to appear. For example, friend recommendation based on geographic location information, friend recommendation based on the same Tag information, friend recommendation based on common concern, microblog topic recommendation based on topic popularity, etc. However, these personalized recommendation technologies usually only consider a certain part of the blogger. One-sided information, but ignores an important purpose, whether the recommended account or topic can be accepted by blogg...

AI Technical Summary

Problems solved by technology

[0004] In addition, the personalized service in Weibo faces other challenges brought about by the rapid development of Weibo

Bloggers are growing rapidly, and they have massive amounts of data in general. All kinds of information are uneven, and many false information and fake accounts are mixed in. If the recommendation system recommends information indiscriminately, it will inevitably affect the use of normal bloggers. Poor blogger experience

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