Digital Content Recommender on the Internet

  • Authors:
  • Sung Ho Ha

  • Affiliations:
  • Kyungpook National University

  • Venue:
  • IEEE Intelligent Systems
  • Year:
  • 2006

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Abstract

While most techniques for recommending digital content have focused on content's similarity, this system makes recommendations to users on the basis of their preferences. The author's personalization system adopts a methodology applicable for Internet service providers as well as news sites. A user preference score prioritizes recommended articles according to their relevance to the user's preferences. A prototype system, applied to an English news site on the Internet, tests the methodology's feasibility and effectiveness.