Tag Correspondence Model for User Tag Suggestion
Tag Correspondence Model for User Tag Suggestion
复制标题
用户标签建议的标签对应模型
DOI:
10.1007/s11390-015-1582-6
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发表时间:
2015-09
影响因子:
0.7
通讯作者:
孙茂松
中科院分区:
文献类型:
--
作者:
涂存超;刘知远;孙茂松
Some microblog services encourage users to annotate themselves with multiple tags, indicating their attributes and interests. User tags play an important role for personalized recommendation and information retrieval. In order to better understand the semantics of user tags, we propose Tag Correspondence Model (TCM) to identify complex correspondences of tags from the rich context of microblog users. The correspondence of a tag is referred to as a unique element in the context which is semantically correlated with this tag. In TCM, we divide the context of a microblog user into various sources (such as short messages, user profile, and neighbors). With a collection of users with annotated tags, TCM can automatically learn the correspondences of user tags from multiple sources. With the learned correspondences, we are able to interpret implicit semantics of tags. Moreover, for the users who have not annotated any tags, TCM can suggest tags according to users’ context information. Extensive experiments on a real-world dataset demonstrate that our method can efficiently identify correspondences of tags, which may eventually represent semantic meanings of tags.
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发表时间:
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