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An Agent-Based Recommender System to Support Collaborative Web Search Based on Shared User Interests

  • Daniela Godoy
  • Analía Amandi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4715)

Abstract

Personal information agents emerged in the last decade as an alternative to assist users to cope with the increasing volume of information available on the Web. In order to provide personalized assistance, these agents rely on user profiles modeling user information preferences, interests and habits. Inserted in communities of people with similar interests, personal agents can improve their assistance by gathering knowledge extracted from the observed common behaviors of single users. In this paper we propose an agent-based recommender system for supporting collaborative Web search in groups of users with partial similarity of interests. Empirical evaluation demonstrates that the interaction among personal agents increases the performance of the overall recommender system.

Keywords

Recommender System Personal Agent Target User Semantic Concept User Interest 
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 2007

Authors and Affiliations

  • Daniela Godoy
    • 1
    • 2
  • Analía Amandi
    • 1
    • 2
  1. 1.ISISTAN Research Institute, UNICEN University, Campus Universitario, Paraje Arroyo Seco, CP 7000, Tandil, Bs. As.Argentina
  2. 2.CONICET, Consejo Nacional de Investigaciones Científicas y Técnicas, CP 1033, Capital Federal, Bs. As.Argentina

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