Who will follow your shop? Exploiting multiple information sources in finding followers

ISCAS OpenIR

	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
页码	401-415
会议日期	April 22, 2013 - April 25, 2013
会议地点	Wuhan, China
收录类别	EI
出版地	Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany
ISSN	3029743
ISBN	9783642374494
部门归属	(1) Xpress Internet Services, Nokia, Beijing, China; (2) Computer Network Information Center, Chinese Academy of Sciences, China; (3) Advanced Analytics Institute, University of Technology Sydney, Australia; (4) Beijing NoyaXe Technologies Co. Ltd., China; (5) Institute of Software, Chinese Academy of Sciences, China
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.; 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.
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16674
专题	中国科学院软件研究所
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]. Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany,2013:401-415.