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Using User Profiles in Intelligent Information Retrieval

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Foundations of Intelligent Systems (ISMIS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2366))

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Abstract

Personalization has been recently one of the most important features of intelligent information retrieval. An intelligent system should store information about user interests and utilize this information to deliver to the user documents he really needs. In such a system the information needs of a user should be represented by means of so called a user profile. User profiles, in other hand, should be used together with queries to sort retrieved information in such order that is adequate to user preferences. In this paper a vector-based information system model is presented, in which the user information needs and preferences (profiles) are defined and the methods for updating user profiles and automatic learning about user preferences are worked out.

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References

  1. Chen L., Sycara K.: Webmate-Personal Agent for Browsing and Searching. In: Proceedings of the Second International Conference on Autonomous Agents, St. Paul, MN, May, ACM Press, New York (1998) 132–139.

    Chapter  Google Scholar 

  2. Chen Z.: Multiplicative adaptive algorithms for user preference retrieval. In Proceedings of the Seventh Annual International Computing and Combinatorics Conference, Springer-Verlag (2001).

    Google Scholar 

  3. Chen Z., Zhu B.: Some Formal Analysis of Rocchio’s Similarity-Based Relevance Feedback Algorithm. Lecture Notes in Computer Science 1969 (2000) 108–119.

    Google Scholar 

  4. Daniłowicz C: Modeling of User Preferences and Needs in Boolean Retrieval Systems. Information Processing & Management, 30 (1994) 363–378.

    Article  Google Scholar 

  5. Daniłowicz C: Models of Information Retrieval Systems with Special Regard to Users’ Preferences. Scientific Papers of the Main Library and Scientific Information Center of the Wrocław University of Technology No.6, Monographs No.3, Wrocław (1992).

    Google Scholar 

  6. Daniłowicz C, Nguyen H.C.: User Profile in Information retrieval Systems. In: Proceedings of the 23rd International Scientific School ISAT 2001, PWr Press (2001) 117–124.

    Google Scholar 

  7. Kok A.J., Botman A.M.: Retrieval Based on User Behavior. In: Proceedings of the 11th ACM Annual International Conference SIGIR, France (1988) 343–357.

    Google Scholar 

  8. McElligot M., Sorensen H.: An Evolutionary Connectionist Approach to Personal Information Filtering. In: Proceeding of the Fourth Irish Neural Network Conference, Dublin, Ireland (1994) 141–146.

    Google Scholar 

  9. Myaeng S.H., Korfhage R.R.: Integration of User Profiles: Models and Experiments in Information Retrieval. Information Processing & Management 26 (1990) 719–738.

    Article  Google Scholar 

  10. Nguyen H.C.: Model of Fuzzy Information Retrieval System Using User Profile. In: Proceedings of the First MISSI National Conference, Wrocław University of Technology, 1998, PWr Press (1998) 179–187.

    Google Scholar 

  11. Nguyen N.T.: Using Consensus Methods for Solving Conflicts of Data in Distributed Systems. Lecture Notes in Artificial Intelligence 1963 (2000) 409–417.

    Google Scholar 

  12. Stadnyk I., Kass R.: Modeling Users’ Interests in Information Filters. Communications of the ACM 35 (1992) 49–50.

    Article  Google Scholar 

  13. Wang Z.W., Wong S.K.M., Yao Y.Y.: An Analysis of Vector Space Models Based on Computational Geometry. In: Proceedings of the 15th ACM Annual International Conference SIGIR, Denmark (1992) 152–160.

    Google Scholar 

  14. Widyantoro D.H.: Dynamic Modeling and Learning User Profile in Personal News Agent. Master Thesis, Dept. of Computer Science, Texas A&M University (1999).

    Google Scholar 

  15. Wong S.K.M., Ziarko W.: On Modeling of Information Retrieval Concepts in Vector Spaces. ACM Transactions on Database Systems, 12 (1987) 299–321.

    Article  Google Scholar 

  16. Wong S.K.M., Yao Y.Y., Bollmann P. Linear structures in information retrieval. In Proceedings of the 1988 ACM-SIGIR Conference on Information Retrieval (1988) 219–232.

    Google Scholar 

  17. Young W.S., Byoung T.Z.: A Reinforcement Learning Agent for Personalized Information Filtering. In: Proceedings of the 2000 ACM International Conference on Intelligent User Interfaces (2000) 248–251.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information Systems, Wrocław University of Technology, Wyb. St. Wyspianskiego 27, 50-370, Wrocław, Poland

    Czesław Daniłowicz & Huy Cuong Nguyen

Authors
  1. Czesław Daniłowicz
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  2. Huy Cuong Nguyen
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Editor information

Editors and Affiliations

  1. UFR d’Informatique, Université Claude Bernard Lyon I, 8, boulevard Niels Bohr, 69622, Villeurbanne Cedex, France

    Mohand-Saïd Hacid

  2. Dept. of Computer Science College of IT, University of North Carolina, Charlotte, NC, 28223, USA

    Zbigniew W. Raś

  3. Băt. L. Equipe de Recherche en Ingénierie des Connaissances, Université Lumière Lyon 2, 5, avenue Pierre Mendes-France, 69676, Bron Cedex, France

    Djamel A. Zighed

  4. LRI, Université Paris Sud, Băt. 490, 91405, Orsay Cedex, France

    Yves Kodratoff

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© 2002 Springer-Verlag Berlin Heidelberg

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Daniłowicz, C., Nguyen, H.C. (2002). Using User Profiles in Intelligent Information Retrieval. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_26

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  • DOI: https://doi.org/10.1007/3-540-48050-1_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43785-7

  • Online ISBN: 978-3-540-48050-1

  • eBook Packages: Springer Book Archive

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