Abstract：In Flickr,one of the most popular photo service websites,groups are superior for photos′ propagation and they can gather photos of similar themes,which brings convenience to users′ easy browsing. Therefore,many researchers are studying how to help users to find out which groups they may be interested in. In this paper,a probabilistic matrix factorization (PMF)based model is proposed for Flickr group recommendation by employing the information of users′ contacts and tags in group. The complexity analysis indicates that the proposed model is efficient and it can be applied to large datasets. The experimental results on a Flickr dataset show the effectiveness of the proposed model. Finally,a Flickr group recommendation system is developed based on the proposed model.
包红云，李秋丹，高珩，郑楠. 集成组内标签与用户链接关系的Flickr组推荐模型[J]. 模式识别与人工智能, 2013, 26(2): 176-181.
BAO Hong-Yun,LI Qiu-Dan,GAO Heng,ZHENG Nan. Flickr Group Recommendation Model by Integrating Tags in Group and Users′ Contacts. , 2013, 26(2): 176-181.
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2013, Vol. 26 
