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First Order Hidden Markov Model for Automatic Arabic Name Entity Recognition

by Fadl Dahan, Ameur Touir, Hassan Mathkour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 7
Year of Publication: 2015
Authors: Fadl Dahan, Ameur Touir, Hassan Mathkour
10.5120/ijca2015905397

Fadl Dahan, Ameur Touir, Hassan Mathkour . First Order Hidden Markov Model for Automatic Arabic Name Entity Recognition. International Journal of Computer Applications. 123, 7 ( August 2015), 37-40. DOI=10.5120/ijca2015905397

@article{ 10.5120/ijca2015905397,
author = { Fadl Dahan, Ameur Touir, Hassan Mathkour },
title = { First Order Hidden Markov Model for Automatic Arabic Name Entity Recognition },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 7 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number7/21974-2015905397/ },
doi = { 10.5120/ijca2015905397 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:04.222828+05:30
%A Fadl Dahan
%A Ameur Touir
%A Hassan Mathkour
%T First Order Hidden Markov Model for Automatic Arabic Name Entity Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 7
%P 37-40
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Name Entity Recognition (NER) is an important process used for several type of applications such as Information Extraction, Information Retrieval, Question Answering, text clustering, etc. It is intended to identify and classify name entities from a given text. NER is performed by using a rule-based approach that relies on human intuitive or machine learning methods such as Hidden Markov Model (HMM), Maximum Entropy (ME), and Decision tree (DT). In this paper, we describe a model based on the first order HMM to recognize name entity in the Arabic language. The model is based on stemming process that solves Arabic's inflection problem and ambiguity. To the best of our knowledge, no work uses this approach for the Arabic language has been reported.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hidden Markov Model (HMM) Name Entity Recognition (NER) Bigram Model.

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