Tag Dispatch Model with Social Network Regularization for Microblog User Tag Suggestion
نویسندگان
چکیده
Microblog is a popular Web 2.0 service which reserves rich information about Web users. In a microblog service, it is a simple and effective way to annotate tags for users to represent their interests and attributes. The attributes and interests of a microblog user usually hide behind the text and network information of the user. In this paper, we propose a probabilistic model, Network-Regularized Tag Dispatch Model (NTDM), for microblog user tag suggestion. NTDM models the semantic relations between words in user descriptions and tags, and takes the social network structure as regularization. Experiments on a real-world dataset demonstrate the effectiveness and efficiency of NTDM compared to other baseline methods. TITLE AND ABSTRACT IN CHINESE ^uÆ^rI\í ¬ ä Kz I\©u . Æ ́Web2.0 A^§Ù¥1 ́L ä^r&E"3Æ¥§I\ ́ «L«^r, Úá5 {ük a"Æ^r á5Ú, ǑÏ~Û õ3 / ̈ © Ú ä¥" ©JÑ«VÇ .§ ä Kz I\©u . £NTDM¤§^5?1Æ^rI\í"NTDMé^r<0 ¥ ÚI\m Â'X?1ï §ÓòÙ¤3 ä( &EÏL Kz aÄ?5"3ý¢êâ þ ¢ L2§NTDMÙ {'\k "
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