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User Models and Regression Methods in Information Retrieval From the Internet

  • Conference paper
UM99 User Modeling

Part of the book series: CISM International Centre for Mechanical Sciences ((CISM,volume 407))

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Abstract

This research focuses on learning a semantic representation of the user’s information needs from a database of relevant documents and queries the in the presence of hierarchically structured semantic classes and lexical databases. The resulting user model will be enhanced by regression methods applied to capturing the syntactic structure of the documents.

This research has been inspired by the members of my Ph.D. committee: Dr. S. Lytinen (DePaul University), Dr. G. Knafl (DePaul University), Dr. B. Mobasher (DePaul University).

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References

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Author information

Authors and Affiliations

  1. Institute for Applied Artificial Intelligence School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA

    Jacek Brzezinski

Authors
  1. Jacek Brzezinski
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Editor information

Editors and Affiliations

  1. University of Sydney, Australia

    Judy Kay

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© 1999 Springer Science+Business Media New York

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Brzezinski, J. (1999). User Models and Regression Methods in Information Retrieval From the Internet. In: Kay, J. (eds) UM99 User Modeling. CISM International Centre for Mechanical Sciences, vol 407. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2490-1_38

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  • DOI: https://doi.org/10.1007/978-3-7091-2490-1_38

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83151-9

  • Online ISBN: 978-3-7091-2490-1

  • eBook Packages: Springer Book Archive

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