open access

https://hdl.handle.net/2115/52024

Performance Evaluation of Recommendation Algorithms Based on Rating-recommendation Interaction

日本語

2009-03-27

情報処理学会

情報処理学会論文誌. 数理モデル化と応用

2(2)

47-57

The problem of information overload spreading across the Internet has been causing serious inefficiency in browsing and searching for information. As a way to overcome the problem, the recommender systems are recently used in many E-commerce sites. Many algorithms have been proposed to improve the accuracy of recommendation based on user ratings. The relation between recommender systems and users is rather interactive in the sense that recommendations decides which items are recommended to users and the results of ratings by users will affect the next recommendations. However, conventional studies have not considered the interactive aspects so much. Therefore, our aim of this paper is to propose a new evaluation model using multiagent modeling where the recommender system and agents (as users) interacts with each other. The properties of typical recommendation algorithms such as user-based and itembased collaborative filtering will be analyzed with our proposed model. Our results also suggest the possibilities to propose a novel and effective recommendation algorithm.

学術雑誌論文

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