UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRBF06053


Registration ID:
205855

Page Number

271-278

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Title

A NOVEL APPROACH FOR ENTITY EXTRACTION IN CODE MIXED DATA

Abstract

In the field of Natural Language Processing (NLP), Named Entity Recognition (NER) is one of the major task. The main challenge in this extraction is to extract Entities that lies in the inadequate information available in a tweet. There has been plenty of work done on this domain of entity extraction but it was mainly focused on popular languages such as English. In general extraction of entities from an informal text makes it difficult and for data that is written in two or more languages (code-mixed) makes it more difficult. In this paper the author has proposed the Machine Learning algorithms like Decision tree, and Conditional Random Field (CRF) with efficiencies of 60% and 76% respectively. The dataset was collected from FIRE-2016.

Key Words

Social media text, Entity extraction, Code-mixed data, CRF, BIO format, Decision Tree

Cite This Article

"A NOVEL APPROACH FOR ENTITY EXTRACTION IN CODE MIXED DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.271-278, April-2019, Available :http://www.jetir.org/papers/JETIRBF06053.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A NOVEL APPROACH FOR ENTITY EXTRACTION IN CODE MIXED DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp271-278, April-2019, Available at : http://www.jetir.org/papers/JETIRBF06053.pdf

Publication Details

Published Paper ID: JETIRBF06053
Registration ID: 205855
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier):
Page No: 271-278
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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