Multi-Class Classification in Natural Language Processing
Even-Zuhar, Yair
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Permalink
https://hdl.handle.net/2142/81592
Description
Title
Multi-Class Classification in Natural Language Processing
Author(s)
Even-Zuhar, Yair
Issue Date
2001
Doctoral Committee Chair(s)
Roth, Dan
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Language, Linguistics
Language
eng
Abstract
This thesis presents theoretical and empirical arguments for the advantages of using: (i) Sentence structure. (ii) The Sequential Model . Empirical arguments are given using word-prediction and part of speech tagging tasks. Theoretical arguments present this thesis as an extension of the current classification methods which aim at disambiguating among many classes.
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