Research Article
Named Entity Recognition using Statistical Model Approach
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 73 - Issue 14 |
| Published: July 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 },
year = { 2013 },
volume = { 73 },
number = { 14 },
pages = { 31-33 },
doi = { 10.5120/12810-0066 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Pyari Padmanabhan
%T Named Entity Recognition using Statistical Model Approach%T
%J International Journal of Computer Applications
%V 73
%N 14
%P 31-33
%R 10.5120/12810-0066
%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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