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Article
Adaptive Information Filtering: Evolutionary Computation and n-gram Representation
Proceedings of the 12th Belgium-Netherlands Artificial Intelligence Conference, 2000
  • Daniel R. Tauritz, Missouri University of Science and Technology
  • Ida G. Sprinkhuizen-Kuyper
Editor(s)
Antal van den Bosch and Hans Weigand
Abstract
Adaptive Information Filtering (AIF) is concerned with filtering information streams in changing environments. The changes may occur both on the transmission side (the nature of the streams can change) and on the reception side (the interests of a user can change). The research described in this paper details the progress made in a prototype AIF system based on weighted n-gram analysis and evolutionary computation. A major advance is the design and implementation of an n-gram class library allowing experimentation with different values of n instead of solely with 3-grams as in the past. The new prototype system was tested on the Reuters-21578 text categorization test collection.
Meeting Name
12th Belgium-Netherlands Artificial Intelligence Conference (BNAIC '00) (2000: Nov. 1-2, Kaatsheuvel, The Netherlands)
Department(s)
Computer Science
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Publication Date
1-1-2000
Disciplines
Citation Information
Daniel R. Tauritz and Ida G. Sprinkhuizen-Kuyper. "Adaptive Information Filtering: Evolutionary Computation and n-gram Representation" Proceedings of the 12th Belgium-Netherlands Artificial Intelligence Conference, 2000 (2000) p. 157 - 164 ISSN: 1568-7805
Available at: http://works.bepress.com/daniel-tauritz/11/