Research on Recommendation List Diversity of Recommender Systems Export

@proceedings{citeulike:3799101, abstract = {Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. Most research up to this point has focused on improving the accuracy of recommender systems. However, considering the range of user\&\#x02019;s interests covered, recommendation diversity is also important. In this paper we propose a novel topic diversity metric which explores hierarchical domain knowledge, and evaluate the recommendation diversity of the two most classic Collaborative filtering (CF) algorithm with movielens dataset}, author = {Zhang, Fuguo}, booktitle = {Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on}, citeulike-article-id = {3799101}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICMECG.2008.32}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4656598}, doi = {10.1109/ICMECG.2008.32}, journal = {Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on}, keywords = {diversity, recommender}, pages = {72--76}, posted-at = {2008-12-16 23:56:19}, priority = {2}, title = {Research on Recommendation List Diversity of Recommender Systems}, url = {http://dx.doi.org/10.1109/ICMECG.2008.32}, year = {2008} }

TY - CONF ID - citeulike:3799101 L3 - citeulike-article-id:3799101 N2 - Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. Most research up to this point has focused on improving the accuracy of recommender systems. However, considering the range of user’s interests covered, recommendation diversity is also important. In this paper we propose a novel topic diversity metric which explores hierarchical domain knowledge, and evaluate the recommendation diversity of the two most classic Collaborative filtering (CF) algorithm with movielens dataset JF - Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on EP - 76 TI - Research on Recommendation List Diversity of Recommender Systems T2 - Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on SP - 72 KW - diversity KW - recommender AU - Zhang, Fuguo PY - 2008/// UR - http://dx.doi.org/10.1109/ICMECG.2008.32 ER -