Publication Type:

Conference Paper

Source:

ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, p.436-438 (2009)

ISBN:

9780769538457

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-73849122163&partnerID=40&md5=266db5c500d3250a2e87f8e0b94999dc

Keywords:

Corpus size, Learning algorithms, Learning systems, Machine learning techniques, PoS taggers, Training and testing

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.

Notes:

cited By 3; Conference of ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing ; Conference Date: 27 October 2009 Through 28 October 2009; Conference Code:78825

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.

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