Paper: Categorization of Turkish News Documents with Morphological Analysis

ACL ID P13-3001
Title Categorization of Turkish News Documents with Morphological Analysis
Venue Annual Meeting of the Association of Computational Linguistics
Session Student Session
Year 2013
Authors

Morphologically rich languages such as Turkish may benefit from morphological analysis in natural language tasks. In this study, we examine the effects of morpho- logical analysis on text categorization task in Turkish. We use stems and word cate- gories that are extracted with morphologi- cal analysis as main features and compare them with fixed length stemmers in a bag of words approach with several learning algorithms. We aim to show the effects of using varying degrees of morphological information.