Genetic Algorithm (GA) in Feature Selection for CRF Based Manipuri Multiword Expression (MWE) Identification

This paper deals with the identification of Multiword Expressions (MWEs) in Manipuri, a highly agglutinative Indian Language. Manipuri is listed in the Eight Schedule of Indian Constitution. MWE plays an important role in the applications of Natural Language Processing(NLP) like Machine Translation, Part of Speech tagging, Information Retrieval, Question Answering etc. Feature selection is an important factor in the recognition of Manipuri MWEs using Conditional Random Field (CRF). The disadvantage of manual selection and choosing of the appropriate features for running CRF motivates us to think of Genetic Algorithm (GA). Using GA we are able to find the optimal features to run the CRF. We have tried with fifty generations in feature selection along with three fold cross validation as fitness function. This model demonstrated the Recall (R) of 64.08%, Precision (P) of 86.84% and F-measure (F) of 73.74%, showing an improvement over the CRF based Manipuri MWE identification without GA application.Comment: 14 pages, 6 figures, see http://airccse.org/journal/jcsit/1011csit05.pd

A Transliteration of CRF based Manipuri POS Tagging

AbstractTransliteration is common to all those language which have multiple scripts. Manipuri, which is one of the Schedule Indian Languages, is one of them. This language has two scripts: a borrowed Bengali Script and the original Meitei Mayek (Script). Part of Speech (POS) tagging of the Bengali Script Manipuri text is performed using Conditional Random Field (CRF) which is then followed by the transliteration to Meitei Mayek

Automatic Segmentation of Manipuri (Meiteilon) Word into Syllabic Units

The work of automatic segmentation of a Manipuri language (or Meiteilon) word into syllabic units is demonstrated in this paper. This language is a scheduled Indian language of Tibeto-Burman origin, which is also a very highly agglutinative language. This language usages two script: a Bengali script and Meitei Mayek (Script). The present work is based on the second script. An algorithm is designed so as to identify mainly the syllables of Manipuri origin word. The result of the algorithm shows a Recall of 74.77, Precision of 91.21 and F-Score of 82.18 which is a reasonable score with the first attempt of such kind for this language.Comment: 12 Pages, 5 Tables See the link http://airccse.org/journal/jcsit/0612csit11.pd

Named Entity Recognition for Manipuri Using Support Vector Machine

PACLIC 23 / City University of Hong Kong / 3-5 December 200

AUTOMATIC SEGMENTATION OF MANIPURI (MEITEILON) WORD INTO SYLLABIC UNITS

ABSTRAC