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	Who will follow your shop? Exploiting multiple information sources in finding followers
	Wu, Liang (2) ; Chin, Alvin (1) ; Xu, Guandong (3) ; Du, Liang (5) ; Wang, Xia (4) ; Meng, Kangjian (4) ; Guo, Yonggang (4) ; Zhou, Yuanchun (2)
	2013
会议名称	18th International Conference on Database Systems for Advanced Applications, DASFAA 2013
会议日期	April 22, 2013 - April 25, 2013
会议地点	Wuhan, China
页码	401-415
中文摘要	WuXianGouXiang is an O2O(offline to online and vice versa)-based mobile application that recommends the nearby coupons and deals for users, by which users can also follow the shops they are interested in. If the potential followers of a shop can be discovered, the merchant's targeted advertising can be more effective and the recommendations for users will also be improved. In this paper, we propose to predict the link relations between users and shops based on the following behavior. In order to better model the characteristics of the shops, we first adopt Topic Modeling to analyze the semantics of their descriptions and then propose a novel approach, named INtent Induced Topic Search (INITS) to update the hidden topics of the shops with and without a description. In addition, we leverage the user logs and search engine results to get the similarity between users and shops. Then we adopt the latent factor model to calculate the similarity between users and shops, in which we use the multiple information sources to regularize the factorization. The experimental results demonstrate that the proposed approach is effective for detecting followers of the shops and the INITS model is useful for shop topic inference. © Springer-Verlag 2013.
英文摘要	WuXianGouXiang is an O2O(offline to online and vice versa)-based mobile application that recommends the nearby coupons and deals for users, by which users can also follow the shops they are interested in. If the potential followers of a shop can be discovered, the merchant's targeted advertising can be more effective and the recommendations for users will also be improved. In this paper, we propose to predict the link relations between users and shops based on the following behavior. In order to better model the characteristics of the shops, we first adopt Topic Modeling to analyze the semantics of their descriptions and then propose a novel approach, named INtent Induced Topic Search (INITS) to update the hidden topics of the shops with and without a description. In addition, we leverage the user logs and search engine results to get the similarity between users and shops. Then we adopt the latent factor model to calculate the similarity between users and shops, in which we use the multiple information sources to regularize the factorization. The experimental results demonstrate that the proposed approach is effective for detecting followers of the shops and the INITS model is useful for shop topic inference. © Springer-Verlag 2013.
收录类别	EI
会议录出版地	Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany
语种	英语
ISSN号	3029743
ISBN号	9783642374494
内容类型	会议论文
源URL	[http://ir.iscas.ac.cn/handle/311060/16674]
专题	软件研究所_软件所图书馆_会议论文
推荐引用方式 GB/T 7714	Wu, Liang ,Chin, Alvin ,Xu, Guandong ,et al. Who will follow your shop? Exploiting multiple information sources in finding followers[C]. 见:18th International Conference on Database Systems for Advanced Applications, DASFAA 2013. Wuhan, China. April 22, 2013 - April 25, 2013.

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