Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Topickr: flickr groups and users reloaded
MM '08 Proceedings of the 16th ACM international conference on Multimedia
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Which photo groups should I choose? A comparative study of recommendation algorithms in Flickr
Journal of Information Science
Recommending Flickr groups with social topic model
Information Retrieval
MultiAspectForensics: mining large heterogeneous networks using tensor
International Journal of Web Engineering and Technology
Combining latent factor model with location features for event-based group recommendation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Unified entity search in social media community
Proceedings of the 22nd international conference on World Wide Web
Image context discovery from socially curated contents
Proceedings of the 21st ACM international conference on Multimedia
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Over the last few years, Flickr has gained massive popularity and groups in Flickr are one of the main ways for photo diffusion. However, the huge volume of groups brings troubles for users to decide which group to choose. In this paper, we propose a tensor decomposition-based group recommendation model to suggest groups to users which can help tackle this problem. The proposed model measures the latent associations between users and groups by considering both semantic tags and social relations. Experimental results show the usefulness of the proposed model.