Improved recommendation based on collaborative tagging behaviors

@inproceedings{citeulike:3212277, abstract = {Considering the natural tendency of people to follow direct or indirect cues of other people's activities, collaborative filtering-based recommender systems often predict the utility of an item for a particular user according to previous ratings by other similar users. Consequently, effective searching for the most related neighbors is critical for the success of the recommendations. In recent years, collaborative tagging systems with social bookmarking as their key component from the suite of Web 2.0 technologies allow users to freely bookmark and assign semantic descriptions to various shared resources on the web. While the list of favorite web pages indicates the interests or taste of each user, the assigned tags can further provide useful hints about what a user thinks of the pages.}, address = {New York, NY, USA}, author = {Zhao, Shiwan and Du, Nan and Nauerz, Andreas and Zhang, Xiatian and Yuan, Quan and Fu, Rongyao }, booktitle = {IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces}, citeulike-article-id = {3212277}, doi = {http://dx.doi.org/10.1145/1378773.1378843}, isbn = {978-1-59593-987-6}, keywords = {recommender, tagging}, location = {Gran Canaria, Spain}, pages = {413--416}, posted-at = {2008-09-10 14:37:46}, priority = {5}, publisher = {ACM}, title = {Improved recommendation based on collaborative tagging behaviors}, url = {http://dx.doi.org/10.1145/1378773.1378843}, year = {2008} }

TY - CONF ID - citeulike:3212277 L3 - citeulike-article-id:3212277 N2 - Considering the natural tendency of people to follow direct or indirect cues of other people's activities, collaborative filtering-based recommender systems often predict the utility of an item for a particular user according to previous ratings by other similar users. Consequently, effective searching for the most related neighbors is critical for the success of the recommendations. In recent years, collaborative tagging systems with social bookmarking as their key component from the suite of Web 2.0 technologies allow users to freely bookmark and assign semantic descriptions to various shared resources on the web. While the list of favorite web pages indicates the interests or taste of each user, the assigned tags can further provide useful hints about what a user thinks of the pages. CY - Gran Canaria, Spain SN - 978-1-59593-987-6 AD - New York, NY, USA EP - 416 TI - Improved recommendation based on collaborative tagging behaviors PB - ACM T2 - IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces SP - 413 KW - recommender KW - tagging AU - Zhao, Shiwan AU - Du, Nan AU - Nauerz, Andreas AU - Zhang, Xiatian AU - Yuan, Quan AU - Fu, Rongyao PY - 2008/// UR - http://dx.doi.org/10.1145/1378773.1378843 ER -