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Reseach Article
Article:Part of Speech Taggers for Morphologically Rich Indian Languages: A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 6 - Number 5 |
| Year of Publication: 2010 |
| Authors: Dinesh Kumar, Gurpreet Singh Josan |
10.5120/1078-1409
|
Dinesh Kumar, Gurpreet Singh Josan . Article:Part of Speech Taggers for Morphologically Rich Indian Languages: A Survey. International Journal of Computer Applications. 6, 5 ( September 2010), 1-9. DOI=10.5120/1078-1409
Abstract
The problem of tagging in natural language processing is to find a way to tag every word in a text as a particular part of speech, e.g., proper pronoun. POS tagging is a very important preprocessing task for language processing activities. This paper reports about the Part of Speech (POS) taggers proposed for various Indian Languages like Hindi, Punjabi, Malayalam, Bengali and Telugu. Various part of speech tagging approaches like Hidden Markov Model (HMM), Support Vector Model (SVM), Rule based approaches, Maximum Entropy (ME) and Conditional Random Field (CRF) have been used for POS tagging. Accuracy is the prime factor in evaluating any POS tagger so the accuracy of every proposed tagger is also discussed in this paper.
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