World Muiticonference on Systemics, Cybernetics and Informatics (SCI-2000)
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Orlando, Florida, United States
アブストラクト
Collaborative filtering, often used in E-commerce applications, is a method to group similar consumers based on their profiles, characteristics or attitudes on specific subjects. This paper proposes a novel method to implement dynamic collaborative filtering by Genetics-based machine learning, in which we employ Organizational-learning oriented Classifier System (OCS) [Takadama 99]. The characteristics of the proposed method for dynamic collaborative filtering are summarized as follows: (1) The proposed method is effective in distributed computer environments with PCs for small number of users. We do not require a centralized database or data management. (2) It learns users' profiles from the individual behaviors of them then generates the recommendation/advice for each people.
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