Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining

P Kalaivani,K L Shunmuganathan

doi:10.1155/2015/961454

P Kalaivani, K L Shunmuganathan

Open Access

https://doi.org/10.1155/2015/961454

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Abstract

With the rapid growth of websites and web form the number of product reviews is available on the sites. An opinion mining system is needed to help the people to evaluate emotions, opinions, attitude, and behavior of others, which is used to make decisions based on the user preference. In this paper, we proposed an optimized feature reduction that incorporates an ensemble method of machine learning approaches that uses information gain and genetic algorithm as feature reduction techniques. We conducted comparative study experiments on multidomain review dataset and movie review dataset in opinion mining. The effectiveness of single classifiers Naïve Bayes, logistic regression, support vector machine, and ensemble technique for opinion mining are compared on five datasets. The proposed hybrid method is evaluated and experimental results using information gain and genetic algorithm with ensemble technique perform better in terms of various measures for multidomain review and movie reviews. Classification algorithms are evaluated using McNemar’s test to compare the level of significance of the classifiers.

Highlights

A basic task in sentiment classification is classifying the polarity of a given text in the document, sentence, or feature level, whether the expressed opinion in a review document, a sentence, or an entity feature is positive, negative, or neutral
We propose the use of genetic algorithm to improve the performance of opinion mining and to address the problems in sentiment analysis
We used Cornell movie review datasets and the multidomain dataset which are frequently used in the sentiment classification

Summary

Introduction

A basic task in sentiment classification is classifying the polarity of a given text in the document, sentence, or feature level, whether the expressed opinion in a review document, a sentence, or an entity feature is positive, negative, or neutral. The WWW is frequently used medium for exchanging the opinions of user reviews about the product, movie, and music. It provides a review text containing consumer opinions, emotions, and service opinions stored in websites, blogs, and web forms. Sentiment analysis is one of the applications of natural language processing and text analytics to identify and extract subjective information in the source materials. It aims to determine the attitude of a writer with respect to some topic or the overall polarity of a document [1,2,3]. Sentiment analysis or opinion mining plays an important role and is difficult to analyze a lot of information individually

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