A sequence labeling approach to morphological analyzer for Tamil language
M. Anand Kumar, Dhanalakshmi, K. P. Soman, Suresh Rajendran · 2010
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. Keywordsmorphology; morphological analyzer; machine learning; sequence labeling.