Collaborative Tagging in Recommender Systems Export

@incollection{citeulike:3979768, abstract = {This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users' preferences for items. In addition, we explore several advantages of collaborative tagging for future searching and information sharing which is used for automatic analysis of user preference and recommendation. We present empirical experiments using real dataset from del.icio.us to demonstrate our algorithm and evaluate performance compared with existing works.}, author = {Ji, Ae-Ttie and Yeon, Cheol and Kim, Heung-Nam and Jo, Geun-Sik}, citeulike-article-id = {3979768}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-76928-6_39}, citeulike-linkout-1 = {http://www.springerlink.com/content/92p8ux6315126547}, doi = {10.1007/978-3-540-76928-6_39}, journal = {AI 2007: Advances in Artificial Intelligence}, keywords = {recommender, tagging}, pages = {377--386}, posted-at = {2009-07-01 14:57:45}, priority = {3}, title = {Collaborative Tagging in Recommender Systems}, url = {http://dx.doi.org/10.1007/978-3-540-76928-6_39}, year = {2007} }

TY - CHAP ID - citeulike:3979768 L3 - citeulike-article-id:3979768 N2 - This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users’ preferences for items. In addition, we explore several advantages of collaborative tagging for future searching and information sharing which is used for automatic analysis of user preference and recommendation. We present empirical experiments using real dataset from del.icio.us to demonstrate our algorithm and evaluate performance compared with existing works. JF - AI 2007: Advances in Artificial Intelligence EP - 386 TI - Collaborative Tagging in Recommender Systems SP - 377 KW - recommender KW - tagging AU - Ji, Ae-Ttie AU - Yeon, Cheol AU - Kim, Heung-Nam AU - Jo, Geun-Sik PY - 2007/// UR - http://dx.doi.org/10.1007/978-3-540-76928-6_39 ER -