Nanchang: International Conference on Management of E-Commerce and E-Government
Research on recommendation list diversity of recommender systems
作者:
F. G. Zhang
关键词:
electronic commerce；groupware；information filtering；information filters；information retrieval system evaluation；collaborative filtering；electronic commerce；hierarchical domain knowledge；movielens dataset；recommendation list diversity evaluation
摘要:
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 userpsilas 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.
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