Tag recommendation method capable of fusing multi-information-source coupling tensor decomposition

Abstract

The invention discloses a tag recommendation method capable of fusing multi-information-source coupling tensor decomposition. The method comprises the following steps that: firstly, while a tensor constructed by tag-item-user triple information is subjected to CP (Canonical Polyadic) decomposition, adding three auxiliary information matrixes, including tag and tag, tag and item and tag and user, to participate in joint decomposition, considering a cooccurrence relationship among tags and the semantic similarity of the tag in WordNet while the tag and the tag similarity matrix are constructed,and taking two similar linear sets as final similarity measurement among tags; then, after a problematic loss function is constructed, adopting an ADMM (Alternating Direction Method of Multipliers) algorithm to carry out parameter optimization on the target function; and finally, according to a decomposition completion prediction tensor, more accurately recommending a Top-N tag to the (user, item). By use of the method, the isomeric information of the tag is fused, and the method is applied to each socialized annotation system and exhibits universality.

Description

technical field [0001] The invention relates to a tag recommendation method that integrates multi-information source coupling tensor decomposition, and belongs to the technical field of computer network tagging. Background technique [0002] With the increasing development of Web2.0 websites, the information on the Web grows at an astonishing speed, and the speed of information growth far exceeds people's processing ability. At this time, the recommendation system plays an increasingly important role in the process of effectively processing information. The social tagging system is a typical application of the recommendation system and has developed rapidly, such as last.fm for sharing music, Flicker for sharing pictures, Delicious for sharing bookmarks, etc. In these social tagging systems, users actively generate tags and pass Tags identify, manage, and discover information resources. Tag recommendation is a research hotspot in the current tagging system, which aims to r...

AI Technical Summary

Problems solved by technology

However, the existing tensor decomposition methods still face the problems of extremely sparse data, missing values, and overfitting in the label recommendation process.

[0003] Aiming at the above three problems, the existing tag recommendation methods based on tensor decomposition only utilize the isomorphic auxiliary information between tags-tags, but do not consider the use of heterogeneous auxiliary information between tags-resources and tags-users

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