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User Models and Regression Methods in Information Retrieval From the Internet

  • Jacek Brzezinski
Conference paper
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 407)

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.

Keywords

Information Retrieval User Model Relevant Document Semantic Representation Syntactic Structure 
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.

References

  1. Miller G., (1990) WORDNET: An Online Lexical Database. International Journal of Lexicography 3(1)Google Scholar
  2. Monta M., Shinoda Y. (1984). Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In Croft B., van Rijsbergen C. J., eds., Proceedings of the Seventeenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM 272–281.Google Scholar
  3. Ott L. R. (1988) An Introduction to Statistical Methods and Data Analysis. Duxbury Press. Fourth Edition.Google Scholar
  4. Rich E. (1983) Users are individuals: individualizing user models. International Journal of Man-Machine Studies. 18:199–214.CrossRefGoogle Scholar
  5. Salton G. (1989) Automatic Text Processing. The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley Publishing Company. 313–326.Google Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Jacek Brzezinski
    • 1
  1. 1.Institute for Applied Artificial Intelligence School of Computer ScienceTelecommunications and Information SystemsDePaul UniversityUSA

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