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Improving Existing Punjabi Morphological Analyzer using N-gram

S. K. Sharma1

  1. Dept. of Computer Science and Applications, DAV University, Jalandhar, India.

Correspondence should be addressed to: sanju3916@rediffmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 171-174, Sep-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i9.171174

Online published on Sep 30, 2017

Copyright © S. K. Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. K. Sharma, “Improving Existing Punjabi Morphological Analyzer using N-gram,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.171-174, 2017.

MLA Style Citation: S. K. Sharma "Improving Existing Punjabi Morphological Analyzer using N-gram." International Journal of Computer Sciences and Engineering 5.9 (2017): 171-174.

APA Style Citation: S. K. Sharma, (2017). Improving Existing Punjabi Morphological Analyzer using N-gram. International Journal of Computer Sciences and Engineering, 5(9), 171-174.

BibTex Style Citation:
@article{Sharma_2017,
author = {S. K. Sharma},
title = {Improving Existing Punjabi Morphological Analyzer using N-gram},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2017},
volume = {5},
Issue = {9},
month = {9},
year = {2017},
issn = {2347-2693},
pages = {171-174},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1450},
doi = {https://doi.org/10.26438/ijcse/v5i9.171174}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i9.171174}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1450
TI - Improving Existing Punjabi Morphological Analyzer using N-gram
T2 - International Journal of Computer Sciences and Engineering
AU - S. K. Sharma
PY - 2017
DA - 2017/09/30
PB - IJCSE, Indore, INDIA
SP - 171-174
IS - 9
VL - 5
SN - 2347-2693
ER -

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Abstract

Morphological analysis is an essential tool for almost all Natural Language Processes like POS tagging, Grammar checking, Sentence simplification, generation of Treebank and parsing. In this research article, author has used N-gram statistical technique to improve the existing morphological analyzer. The main factor that reduces the accuracy of morphological analyzer is presence of unknown words. In this research article author has used n-gram approach for detecting the POS tag of unknown word. The results shows an average precision of 82.34, recall 70.20 and F-measure 75.74.

Key-Words / Index Term

Morphological analyzer, Morph, N-gram approach

References

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