IJE TRANSACTIONS B: Applications Vol. 30, No. 11 (November 2017) 1428-1437    Article in Press

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S. KOTAGIRI, M. B. Kalva and M. A
( Received: May 26, 2017 – Accepted: September 08, 2017 )

Abstract    As the internet and its applications are growing, E-commerce has become one of its rapid applications. Customers of E-commerce were provided with theopportunity to express their opinion about theproduct on the web as a text in the form of reviews. In the previous studies, mere founding sentiment from reviews was not helpful to get theexact opinion of the review. In this paper, we have used Aspect-Based Opinion Mining to get more Interesting aspects of a product’ssentiment from unlabelled textual data. First noun phrases algorithm was used to get all the aspect term of a review sentence. Secondly get sentiment algorithm was applied on the result of thenoun-phrase algorithm. Finally using relativeimportance algorithm important aspects were presented to the user. Our proposed methodology has achieved 77.03% of accuracy compared to previews studies. The proposed methodology can be applied for any product reviews in the form of text without any label, and it does not require any training dataset.


Keywords    Sentiment analysis, Opinion mining, Aspect term, Aspect based analysis, Customer review


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