Publication Type : Journal Article
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Publisher : Citeseer
Source : IJCSE) International Journal on Computer Science and Engineering, Citeseer, Volume 2, Number 06, p.1944–195 (2010)
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Year : 2010
Abstract : Morphological analysis is the basic process for any Natural Language Processing task. Morphology is the study of internal structure of the word. Morphological analysis retrieves the grammatical features and properties of a morphologically inflected word. Capturing the agglutinative structure of Tamil words by an automatic system is a challenging job. Generally rule based approaches are used for building morphological analyzer. In this paper we propose a novel approach to solve the morphological analyzer problem using machine learning methodology. Here morphological analyzer problem is redefined as classification problem. This approach is based on sequence labeling and training by kernel methods that captures the non linear relationships of the morphological features from training data samples in a better and simpler way. Keywords- morphology; morphological analyzer; machine learning; sequence labeling...
Cite this Research Publication : A. M Kumar, Dhanalakshmi, V., Dr. Soman K. P., and Rajendran, S., “A sequence labeling approach to morphological analyzer for Tamil language”, IJCSE) International Journal on Computer Science and Engineering, vol. 2, pp. 1944–195, 2010.