Sentiment classification of customer reviews based on fuzzy logic

Citation

Nadali, Samaneh and Azmi Murad, Masrah Azrifah and Abdul Kadir, Rabiah (2010) Sentiment classification of customer reviews based on fuzzy logic. In: International Symposium on Information Technology (ITSim'10), 15-17 June 2010, Kuala Lumpur Convention Centre, Kuala Lumpur. (pp. 1037-1044).

Abstract

Nowadays, e-commerce is growing fast, so product reviews have grown rapidly on the web. The large number of reviews makes it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). Most existing method utilize a list of opinion words for sentiment classification. whereas, this paper propose a fuzzy logic model to perform semantic classifications of customers review into the following sub-classes: very weak, weak, moderate, very strong and strong by combinations adjective, adverb and verb to increase holistic the accuracy of lexicon approach. Fuzzy logic, unlike statistical data mining techniques, not only allows using non-numerical values also introduces the notion of linguistic variables. Using linguistic terms and variables will result in a more human oriented querying process.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Computer Science and Information Technology
DOI Number:	https://doi.org/10.1109/ITSIM.2010.5561583
Publisher:	IEEE
Keywords:	Fuzzy logic; Opinion mining; Sentiment classification
Depositing User:	Nabilah Mustapa
Date Deposited:	21 Jun 2016 04:53
Last Modified:	27 May 2019 02:37
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ITSIM.2010.5561583
URI:	http://psasir.upm.edu.my/id/eprint/47624
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