CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
Cross-Platform Multi-Modal Topic Modeling for Personalized Inter-Platform Recommendation
Min, Weiqing1; Bao, Bing-Kun1; Xu, Changsheng1; Hossain, M. Shamim2
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
2015-10-01
Volume17Issue:10Pages:1787-1801
SubtypeArticle
AbstractIn this paper, we investigate a novel cross-platform multimedia problem: given two platforms, Flickr and Foursquare, we conduct the recommendation between these two platforms, namely the photo recommendation from Flickr to Foursquare users and the venue recommendation from Foursquare to Flickr users. Such inter-platform recommendations enable users from one single platform to enjoy different recommendation services effectively. To solve the problem, we propose a cross-platform multi-modal topic model ((CMTM)-T-3), which is capable of: 1) differentiating between two kinds of topics, i.e., platform-specific topics only relevant to a certain platform and shared topics characterizing the knowledge shared by different platforms and 2) aligning multiple modalities from different platforms. Specifically, (CMTM)-T-3 can not only split the topic space into the shared topic space and platform-specific topic space and learn them simultaneously, but also enable the alignment among different modalities through the learned topic space. Given the location information, we applied the proposed (CMTM)-T-3 into two inter-platform recommendation applications: 1) personalized venue recommendation from Foursquare to Flickr users and 2) personalized image recommendation from Flickr to Foursquare users. We have conducted experiments on the collected large-scale real-world dataset from Flickr and Foursquare. Qualitative and quantitative evaluation results validate the effectiveness of our method and demonstrate the advantage of connecting different platforms with different modalities for the inter-platform recommendation.
KeywordCross-platform Topic Model Recommendation
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TMM.2015.2463226
WOS KeywordNETWORKS
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000361685400009
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9016
Collection模式识别国家重点实验室_多媒体计算与图形学
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.King Saud Univ, SWE Dept, Coll Comp & Informat Sci, Riyadh 11543, Saudi Arabia
Recommended Citation
GB/T 7714
Min, Weiqing,Bao, Bing-Kun,Xu, Changsheng,et al. Cross-Platform Multi-Modal Topic Modeling for Personalized Inter-Platform Recommendation[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2015,17(10):1787-1801.
APA Min, Weiqing,Bao, Bing-Kun,Xu, Changsheng,&Hossain, M. Shamim.(2015).Cross-Platform Multi-Modal Topic Modeling for Personalized Inter-Platform Recommendation.IEEE TRANSACTIONS ON MULTIMEDIA,17(10),1787-1801.
MLA Min, Weiqing,et al."Cross-Platform Multi-Modal Topic Modeling for Personalized Inter-Platform Recommendation".IEEE TRANSACTIONS ON MULTIMEDIA 17.10(2015):1787-1801.
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