A HMM text classification model with learning capacity

A HMM text classification model with learning capacity

In this paper a method of classifying biomedical text documents based on Hidden Markov Model is proposed and evaluated. The method is integrated into a framework named BioClass. Bioclass is composed of intelligent text classification tools and facilitates the comparison between them because it has s...

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Bibliographic Details
Main Authors: Eva L. IGLESIAS, Lourdes BORRAJO, R. ROMERO
Format: Article
Language:English
Published: Ediciones Universidad de Salamanca 2015-05-01
Series:Advances in Distributed Computing and Artificial Intelligence Journal
Subjects:
hidden markov model
text classification
bioinformatics
adaptive models
Online Access:https://revistas.usal.es/index.php/2255-2863/article/view/12690
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spelling doaj-be07150834e545ffa092852f56885b6d2020-11-25T03:06:31ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632015-05-0133213410.14201/ADCAIJ201433213411909A HMM text classification model with learning capacityEva L. IGLESIAS0Lourdes BORRAJO1R. ROMERO2University of VigoUniversity of VigoUniversity of VigoIn this paper a method of classifying biomedical text documents based on Hidden Markov Model is proposed and evaluated. The method is integrated into a framework named BioClass. Bioclass is composed of intelligent text classification tools and facilitates the comparison between them because it has several views of the results. The main goal is to propose a more effective based-on content classifier than current methods in this environment To test the effectiveness of the classifier presented, a set of experiments performed on the OSHUMED corpus are preseted. Our model is tested adding it learning capacity and without it, and it is compared with other classification techniques. The results suggest that the adaptive HMM model is indeed more suitable for document classification.https://revistas.usal.es/index.php/2255-2863/article/view/12690hidden markov modeltext classificationbioinformaticsadaptive models
collection DOAJ
language English
format Article
sources DOAJ
author Eva L. IGLESIAS
Lourdes BORRAJO
R. ROMERO
spellingShingle Eva L. IGLESIAS
Lourdes BORRAJO
R. ROMERO
A HMM text classification model with learning capacity
Advances in Distributed Computing and Artificial Intelligence Journal
hidden markov model
text classification
bioinformatics
adaptive models
author_facet Eva L. IGLESIAS
Lourdes BORRAJO
R. ROMERO
author_sort Eva L. IGLESIAS
title A HMM text classification model with learning capacity
title_short A HMM text classification model with learning capacity
title_full A HMM text classification model with learning capacity
title_fullStr A HMM text classification model with learning capacity
title_full_unstemmed A HMM text classification model with learning capacity
title_sort hmm text classification model with learning capacity
publisher Ediciones Universidad de Salamanca
series Advances in Distributed Computing and Artificial Intelligence Journal
issn 2255-2863
publishDate 2015-05-01
description In this paper a method of classifying biomedical text documents based on Hidden Markov Model is proposed and evaluated. The method is integrated into a framework named BioClass. Bioclass is composed of intelligent text classification tools and facilitates the comparison between them because it has several views of the results. The main goal is to propose a more effective based-on content classifier than current methods in this environment To test the effectiveness of the classifier presented, a set of experiments performed on the OSHUMED corpus are preseted. Our model is tested adding it learning capacity and without it, and it is compared with other classification techniques. The results suggest that the adaptive HMM model is indeed more suitable for document classification.
topic hidden markov model
text classification
bioinformatics
adaptive models
url https://revistas.usal.es/index.php/2255-2863/article/view/12690
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AT lourdesborrajo ahmmtextclassificationmodelwithlearningcapacity
AT rromero ahmmtextclassificationmodelwithlearningcapacity
AT evaliglesias hmmtextclassificationmodelwithlearningcapacity
AT lourdesborrajo hmmtextclassificationmodelwithlearningcapacity
AT rromero hmmtextclassificationmodelwithlearningcapacity
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