Tag recommending system and method based on synergistic topic regression with social regularization

Abstract

The invention discloses a tag recommending system and method based on synergistic topic regression with social regularization. The tag recommending system comprises a CTR (Common Technical Regulation) model establishing module, a CTR model establishing module with social regularization, a parameter studying module and a tag recommending module, wherein the CTR model establishing module is used for establishing CTR models to all tags; the CTR model establishing module with social regularization is used for integrating an article-tag matrix, content information of the articles and a social network of the articles into a level Bayesian model to establish a CTR-SR model; the parameter studying module is used for studying parameters in the model established by the CTR model establishing module with social regularization by utilizing maximum posterior estimation, and finally obtaining the whole posterior probability of all the parameters; the tag recommending module is used for carrying out tag recommendation according to the studied parameters. The tag recommending system and method disclosed by the invention has the advantages that the CTR model is applied in tag recommendation, and the level Bayesian model is provided by expanding the CTR, so that the article-tag matrix and the content information of the articles are effectively integrated, the network relationship among the articles are utilized, and further the accuracy of recommendation is improved.

Description

technical field [0001] The present invention relates to a tag recommendation system and method, in particular to a tag recommendation system and method based on social regularization collaborative topic regression. Background technique [0002] Labeling systems play an important role in classification and organizational systems. For example, Flickr (a photo sharing site) uses tags to organize and categorize images, and Last.fm (an online music library) uses tags to categorize artists and music. CiteULike (personal academic database) allows users to tag articles. Through the tagging system, users can better organize their information and find related items or information more easily. [0003] However, finding labels that accurately describe items can be difficult. Because of this, tag recommendation becomes more and more important. With the tag recommendation system, users only need a few clicks to complete the tagging process. Also, tags generated by different users may...

AI Technical Summary

Problems solved by technology

[0009] However, both the co-occurrence method and the content-based method ignore some useful information, such as the network relationship between items, thus, they cannot achieve satisfactory enough results when applied

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