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Classification of machine learning engines using latent semantic indexing

With the huge increase of software functionalities, sizes and application domain, the difficulty of categorizing and classifying software for information retrieval and maintenance purposes is on demand.This work includes the use of Latent Semantic Indexing (LSI) in classifying neural network and k-...

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Main Authors: Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
QA76 Computer software
Online Access:http://repo.uum.edu.my/10947/1/CR197%281%29.pdf
http://repo.uum.edu.my/10947/
http://www.kmice.uum.edu.my
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spelling my.uum.repo.109472015-05-25T03:23:14Z http://repo.uum.edu.my/10947/ Classification of machine learning engines using latent semantic indexing Yusof, Yuhanis Alhersh, Taha Mahmuddin, Massudi Mohamed Din, Aniza QA76 Computer software With the huge increase of software functionalities, sizes and application domain, the difficulty of categorizing and classifying software for information retrieval and maintenance purposes is on demand.This work includes the use of Latent Semantic Indexing (LSI) in classifying neural network and k-nearest neighborhood source code programs. Functional descriptors of each program are identified by extracting terms contained in the source code.In addition, information on where the terms are extracted from is also incorporated in the LSI.Based on the undertaken experiment, the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm as provided in the Weka tool. 2012-07-04 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/10947/1/CR197%281%29.pdf Yusof, Yuhanis and Alhersh, Taha and Mahmuddin, Massudi and Mohamed Din, Aniza (2012) Classification of machine learning engines using latent semantic indexing. In: Knowledge Management International Conference (KMICe) 2012, 4 – 6 July 2012, Johor Bahru, Malaysia. http://www.kmice.uum.edu.my
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Yusof, Yuhanis
Alhersh, Taha
Mahmuddin, Massudi
Mohamed Din, Aniza
Classification of machine learning engines using latent semantic indexing
description With the huge increase of software functionalities, sizes and application domain, the difficulty of categorizing and classifying software for information retrieval and maintenance purposes is on demand.This work includes the use of Latent Semantic Indexing (LSI) in classifying neural network and k-nearest neighborhood source code programs. Functional descriptors of each program are identified by extracting terms contained in the source code.In addition, information on where the terms are extracted from is also incorporated in the LSI.Based on the undertaken experiment, the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm as provided in the Weka tool.
format Conference or Workshop Item
author Yusof, Yuhanis
Alhersh, Taha
Mahmuddin, Massudi
Mohamed Din, Aniza
author_facet Yusof, Yuhanis
Alhersh, Taha
Mahmuddin, Massudi
Mohamed Din, Aniza
author_sort Yusof, Yuhanis
title Classification of machine learning engines using latent semantic indexing
title_short Classification of machine learning engines using latent semantic indexing
title_full Classification of machine learning engines using latent semantic indexing
title_fullStr Classification of machine learning engines using latent semantic indexing
title_full_unstemmed Classification of machine learning engines using latent semantic indexing
title_sort classification of machine learning engines using latent semantic indexing
publishDate 2012
url http://repo.uum.edu.my/10947/1/CR197%281%29.pdf
http://repo.uum.edu.my/10947/
http://www.kmice.uum.edu.my
_version_ 1644280504226152448
score 13.2014675

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