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Social tagging systems, which allow users to freely annotate online resources with tags, become popular in the Web 2.0 era. In order to ease the annotation process, research on social tag recommendation has drawn much attention in recent years. Modeling the social tagging behavior could better reflect the nature of this issue and improve the result of recommendation. In this paper, we proposed a novel approach for bringing the associative ability to model the social tagging behavior and then todblp:conf/textgraphs/FanXZ12 fatcat:qb5rfuw53nfstaf2x7o5oqb3eq