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Hybrid Collaborative Filtering and Content-Based Filtering for Improved Recommender System

by: Kyung-Yong Jung, Dong-Hyun Park, Jung-Hyun Lee

edited by: Marian Bubak, GeertDick Albada, PeterM Sloot, Jack Dongarra

In Computational Science - ICCS 2004, Vol. 3036 (2004), pp. 295-302, doi:10.1007/978-3-540-24685-5_37  Key: citeulike:12164409

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Abstract

The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, WebBot: Web Robot Agent, which integrates with the web and acts as a personal recommender system that cooperates with the user on identifying interesting pages. Hybrid components from collaborative filtering and content-based filtering, a hybrid recommender system can overcome traditional shortcomings. In this paper, we present an effective hybrid collaborative filtering and content-based filtering for improved recommender system. Experimental results indicate the hybrid collaborative filtering and content-based filtering better than collaborative, content-based, and combined filtering approach.


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