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http://hdl.handle.net/20.500.12358/25202
TitleArabic opinion mining using combined classification approach
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Abstract

In this paper, we present a combined approach that automatically extracts opinions from Arabic documents. Most research efforts in the area of opinion mining deal with English texts and little work with Arabic text. Unlike English, from our experiments, we found that using only one method on Arabic opinioned documents produce a poor performance. So, we used a combined approach that consists of three methods. At the beginning, lexicon based method is used to classify as much documents as possible. The resultant classified documents used as training set for maximum entropy method which subsequently classifies some other documents. Finally, k-nearest method used the classified documents from lexicon based method and maximum entropy as training set and classifies the rest of the documents. Our experiments showed that in average, the accuracy moved (almost) from 50% when using only lexicon based method to 60% when used lexicon based method and maximum entropy together, to 80% when using the three combined methods.

Authors
El-Halees, Alaa M.
TypeJournal Article
Date2011
Subjects
opinion mining
combined classification
arabic opinion mining
sentiment classification
PublisherNaif Arab University for Security Sciences
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  • Staff Publications- Faculty of Information Technology [192]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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