Publication Type : Conference Paper
Publisher : ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing
Source : ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, p.436-438 (2009)
ISBN : 9780769538457
Keywords : Corpus size, Learning algorithms, Learning systems, Machine learning techniques, PoS taggers, Training and testing
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Computer Science, Electronics and Communication
Year : 2009
Abstract : This paper presents the chunker for Tamil using Machine learning techniques. Chunking is the task of identifying and segmenting the text into syntactically correlated word groups. The chunking is done by the machine learning techniques, where the linguistical knowledge is automatically extracted from the annotated corpus. We have developed our own tagset for annotating the corpus, which is used for training and testing the POS tagger generator and the chunker. The present tagset consists of thirty tags for POS and nine tags for chunking. A corpus size of two hundred and twenty five thousand words was used for training and testing the accuracy of the Chunker. We found that CRF++ affords the most encouraging result for Tamil chunker. © 2009 IEEE.
Cite this Research Publication : Va Dhanalakshmi, Padmavathy, Pa, M Kumar, A., Soman, K. Pa, and Rajendran, Sb, “Chunker for Tamil”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009, pp. 436-438.