Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining
Joint Authors
Kalaivani, P.
Shunmuganathan, K. L.
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-14
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Kalaivani, P.& Shunmuganathan, K. L.. 2015. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining. Scientific Programming،Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1076560
Modern Language Association (MLA)
Kalaivani, P.& Shunmuganathan, K. L.. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining. Scientific Programming No. 2015 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1076560
American Medical Association (AMA)
Kalaivani, P.& Shunmuganathan, K. L.. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining. Scientific Programming. 2015. Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1076560
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1076560