Research Article

Design and Evaluation of a Parallel Classifier for Large-Scale Arabic Text

by  Mohammed M. Abu Tair, Rebhi S. Baraka
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Issue 3
Published: August 2013
Authors: Mohammed M. Abu Tair, Rebhi S. Baraka
10.5120/13090-0370
PDF

Mohammed M. Abu Tair, Rebhi S. Baraka . Design and Evaluation of a Parallel Classifier for Large-Scale Arabic Text. International Journal of Computer Applications. 75, 3 (August 2013), 13-20. DOI=10.5120/13090-0370

                        @article{ 10.5120/13090-0370,
                        author  = { Mohammed M. Abu Tair,Rebhi S. Baraka },
                        title   = { Design and Evaluation of a Parallel Classifier for Large-Scale Arabic Text },
                        journal = { International Journal of Computer Applications },
                        year    = { 2013 },
                        volume  = { 75 },
                        number  = { 3 },
                        pages   = { 13-20 },
                        doi     = { 10.5120/13090-0370 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2013
                        %A Mohammed M. Abu Tair
                        %A Rebhi S. Baraka
                        %T Design and Evaluation of a Parallel Classifier for Large-Scale Arabic Text%T 
                        %J International Journal of Computer Applications
                        %V 75
                        %N 3
                        %P 13-20
                        %R 10.5120/13090-0370
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Text classification has become one of the most important techniques in text mining. A number of machine learning algorithms have been introduced to deal with automatic text classification. One of the common classification algorithms is the k-NN algorithm which is known to be one of the best classifiers applied for different languages including Arabic language. However, the k-NN algorithm is of low efficiency because it requires a large amount of computational power. Such a drawback makes it unsuitable to handle a large volume of text documents with high dimensionality and in particular in the Arabic language. This paper introduces a high performance parallel classifier for large-scale Arabic text that achieves the enhanced level of speedup, scalability, and accuracy. The parallel classifier is based on the sequential k-NN algorithm. The classifier has been tested using the OSAC corpus. The performance of the parallel classifier has been studied on a multicomputer cluster. The results indicate that the parallel classifier has very good speedup and scalability and is capable of handling large documents collections with higher classification results.

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Arabic text classification k-NN algorithm parallel classifier multicomputer cluster

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