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

  • Kyung-Yong Jung
  • Dong-Hyun Park
  • Jung-Hyun Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)

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.

Keywords

Active User Recommender System User Preference Collaborative Filter Mean Absolute Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kyung-Yong Jung
    • 1
  • Dong-Hyun Park
    • 2
  • Jung-Hyun Lee
    • 3
  1. 1.HCI Lab., Department of Computer Science & Engineering 
  2. 2.Department of Industrial Engineering 
  3. 3.Department of Computer Science & EngineeringInha UniversityKorea

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