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Opinion Mining of M Learning Reviews using Soft Computing Techniques

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International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 54 - Number 15
Year of Publication: 2012
Authors:
A. Nisha Jebaseeli
E. Kirubakaran
10.5120/8646-2558

Nisha A Jebaseeli and E Kirubakaran. Article: Opinion Mining of M Learning Reviews using Soft Computing Techniques. International Journal of Computer Applications 54(15):44-48, September 2012. Full text available. BibTeX

@article{key:article,
	author = {A. Nisha Jebaseeli and E. Kirubakaran},
	title = {Article: Opinion Mining of M Learning Reviews using Soft Computing Techniques},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {54},
	number = {15},
	pages = {44-48},
	month = {September},
	note = {Full text available}
}

Abstract

Internet has increasingly become the place for online learning, and exchange of ideas. The rapid development in wireless technology offering fast data transfer has lead to mobile device revolution. With the ease of access of mobile devices like mobile phones, PDAs, tablet PCs and high bandwidth through wireless, there is an upsurge of mobile learning or M-learning. It is important to know the opinion of users using m-learning platforms for developing and fine tuning of M-learning systems. The sheer volume of reviews found in the internet blog spot, bulletin board makes it difficult to track and understand customer opinions. Opinion mining also known as sentiment mining is an area of research which attempts at determining the opinion underlying a text written in natural language which summarizes the customer reviews and express whether the opinions are positive or negative. In this paper, we investigate the classification accuracy of machine learning algorithms for opinion mining of M-learning system review.

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