User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System(Artificial Intelligence and Cognitive Science)

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概要

• 論文の詳細を見る

• The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.

• 社団法人電子情報通信学会の論文
• 2004-12-01

著者

• Lee Jung-hyun

  School Of Computer Science & Engineering Inha University

• Jung Kyung-yong

  Hci Lab. Dept. Of Computer Science & Information Engineering Inha University

• Lee Jung-Hyun

  School of Advanced Materials Engineering, Kookmin University, Sungbuk-gu, Seoul 136-702, Korea

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• User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System(Artificial Intelligence and Cognitive Science)

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