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Named Entity Recognition using Statistical Model Approach

by Pyari Padmanabhan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 73 - Number 14
Year of Publication: 2013
Authors: Pyari Padmanabhan
10.5120/12810-0066

Pyari Padmanabhan . Named Entity Recognition using Statistical Model Approach. International Journal of Computer Applications. 73, 14 ( July 2013), 31-33. DOI=10.5120/12810-0066

@article{ 10.5120/12810-0066,
author = { Pyari Padmanabhan },
title = { Named Entity Recognition using Statistical Model Approach },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 73 },
number = { 14 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 31-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume73/number14/12810-0066/ },
doi = { 10.5120/12810-0066 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:40:05.549354+05:30
%A Pyari Padmanabhan
%T Named Entity Recognition using Statistical Model Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 73
%N 14
%P 31-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Named Entities (NE) are atomic elements like names of person, places, locations, organizations, quantity etc. Named Entity Recognition is a classification problem. It involves the task of identifying and classifying certain elements in text into predefined categories of named entities. Main subtasks for the Named Entity Recognition involves (1) The Document corpus construction (2) The preprocessing of the documents (3) Determine the contexts (4) Applying the hidden Markov model. In this paper, the hidden Markov model is adopted for the purpose of effective recognition of Named Entities from a document corpus.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hidden Markov model preprocessing

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