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)


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.


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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baeza-Yates, R., Pino, J.A.: A first step to formally evaluate collaborative work. In: Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work: The Integration Challenge, pp. 56–60. ACM Press, New York (1997)CrossRefGoogle Scholar
  2. 2.
    Balabanovic, M., Shoham, Y.: FAB: Combining content-based and collaborative recommendation. Communications of the ACM 40(3), 66–72 (1997)CrossRefGoogle Scholar
  3. 3.
    Blanzieri, E., Giorgini, P., Massa, P., Recla, S.: Implicit culture for multi-agent interaction support. In: Batini, C., Giunchiglia, F., Giorgini, P., Mecella, M. (eds.) CoopIS 2001. LNCS, vol. 2172, pp. 27–39. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Chau, M., Zeng, D., Chen, H., Huang, M., Hendriawan, D.: Design and evaluation of a multi-agent collaborative Web mining system. Decision Support Systems 35(1), 167–183 (2003)CrossRefGoogle Scholar
  5. 5.
    Giménez-Lugo, G.A., Amandi, A., Sichman, J., Godoy, D.: Enriching information agents’ knowledge by ontology comparison: A case study. In: Garijo, F.J., Riquelme, J.-C., Toro, M. (eds.) IBERAMIA 2002. LNCS (LNAI), vol. 2527, pp. 546–555. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Godoy, D., Amandi, A.: User profiling for web page filtering. IEEE Internet Computing 9(4), 56–64 (2005)CrossRefGoogle Scholar
  7. 7.
    Mitchell, T.M.: Machine Learning. McGraw-Hill, New York (1997)zbMATHGoogle Scholar
  8. 8.
    Rodríguez, M.A., Egenhofer, M.J.: Determining semantic similarity among entity classes from different ontologies. IEEE Transactions on Knowledge and Data Engineering 15(2), 442–456 (2003)CrossRefGoogle Scholar
  9. 9.
    Somlo, G., Howe, A.E.: QueryTracker: An agent for tracking persistent information needs. In: AAMAS 2004. Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 488–495. IEEE Computer Society, Los Alamitos (2004)Google Scholar
  10. 10.
    Turner, R.M., Turner, E.H., Wagner, T.A., Wheeler, T.J., Ogle, N.E.: Using explicit, a priori contextual knowledge in an intelligent Web search agent. In: Akman, V., Bouquet, P., Thomason, R.H., Young, R.A. (eds.) CONTEXT 2001. LNCS (LNAI), vol. 2116, pp. 343–352. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  11. 11.
    Williams, A.B., Ren, Z.: Agents teaching agents to share meaning. In: Proceedings of the 5th International Conference on Autonomous Agents, Montreal, Canada, pp. 465–472. ACM Press, New York (2001)CrossRefGoogle Scholar
  12. 12.
    Yu, B., Singh, P.: An agent-based approach to knowledge management. In: CIKM 2002. Proceedings of the 11th International Conference on Information and Knowledge Management, pp. 642–644 (2002)Google Scholar

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

Personalised recommendations