Date of Award

1-1-2013

Language

English

Document Type

Master's Thesis

Degree Name

Master of Science (MS)

College/School/Department

Department of Computer Science

Content Description

1 online resource (ii, 21 pages) : illustrations (some color)

Dissertation/Thesis Chair

Tomek Strzalkowski

Keywords

genetic algorithm, hedge detection, Hedge (Linguistics), Computational linguistics, Genetic algorithms, Language and the Internet

Subject Categories

Computer Sciences

Abstract

Semantic and syntactic features found in text can be used in combination to statistically predict linguistic devices such as hedges in online chat. Some features are better indicators than others, and there are cases when multiple features need to be considered together to be useful. Once the features are identified, it becomes an optimization problem to find the best division of data.

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