Zhang, Zi-Ke Zhou, Tao Zhang, Yi-Cheng 2011-09-23 In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related studies and future challenges of tag-aware recommendation algorithms. application/pdf https://folia.unifr.ch/global/documents/302200 https://folia.unifr.ch/documents/302200/files/11390_2011_Article_176.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1007/s11390-011-0176-1 info:eu-repo/semantics/openAccess License undefined Journal of Computer Science and Technology. - 2011, vol. 26, no. 5, p. 767-777 social tagging systems tag-aware recommendation network-based/tensor-based/topic-based methods info:eu-repo/classification/udc/53 Tag-aware recommender systems : a state-of-the-art survey http://purl.org/coar/resource_type/c_6501