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University of Illinois at Urbana-Champaign
Multi-Class Classification in Natural Language Processing
Abstract
dc:descriptionThis 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.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Even-Zuhar, Yair
- Contributors dc:contributor
-
- Roth, Dan
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3030430
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81592