Text Classification Methodologies Applied to Micro-Text in Military Chat

Author

Rosa, Kevin Dela ; Ellen, Jeffrey

Author_Institution

Language Technol. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA

fYear

2009

fDate

13-15 Dec. 2009

Firstpage

710

Lastpage

714

Abstract

We propose methods to classify lines of military chat, or posts, which contain items of interest. We evaluated several current text categorization and feature selection methodologies on chat posts. Our chat posts are examples of ´micro-text´, or text that is generally very short in length, semi-structured, and characterized by unstructured or informal grammar and language. Although this study focused specifically on tactical updates via chat, we believe the findings are applicable to content of a similar linguistic structure. Completion of this milestone is a significant first step in allowing for more complex categorization and information extraction.

Keywords

classification; electronic messaging; text analysis; chat posts; feature selection; information extraction; micro-text; military chat; text categorization; text classification; Costs; Data mining; Information analysis; Machine learning; Monitoring; Natural language processing; Speech analysis; Support vector machine classification; Support vector machines; Text categorization; Chat; Micro-text; Naive Bayes; Natural Language Processing; Rocchio; Support Vector Machines; Text Classification; k-Nearest Neighbor;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Applications, 2009. ICMLA '09. International Conference on

Conference_Location

Miami Beach, FL

Print_ISBN

978-0-7695-3926-3

Type

conf

DOI

10.1109/ICMLA.2009.49

Filename

5381337