Title :
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
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;
Conference_Titel :
Machine Learning and Applications, 2009. ICMLA '09. International Conference on
Conference_Location :
Miami Beach, FL
Print_ISBN :
978-0-7695-3926-3
DOI :
10.1109/ICMLA.2009.49
