Collaborative Filtering in Social Tagging Systems Based on Joint Item-Tag Recommendations
Jing Peng, Daniel Zeng, Huimin Zhao, Fei-yue Wang ( CIKM-10 ) http://dl.acm.org/citation.cfm?id=1871541 The paper “Collaborative Filtering in Social Tagging Systems Based on Joint Item-Tag Recommendations” introduces a novel framework for collaborative filtering in social tagging systems. In recent years, social tagging has been gaining wide-spread popularity in a variety of applications. Enabling automated recommendation of various kinds in social tagging systems can further enhance this important social information discovery mechanism. However, all of the previous research focuses on recommendations of either items or tags. If we can leverage tag information and integrate it into our system, it could help to improve the performance of recommendation engine. Firstly, Peng et al. present a structure that integrates all possible co-occurrence information among the three entities (i.e., User, Item, and Tag) into one framework. Different with other work that usually consider o...