Title :
An approach of opinion mining for online marketing using sentiment thesaurus and concept search engine
Author :
P. Ajitha;G. Gunasekaran
Author_Institution :
Sathyabama University, Chennai, India
Abstract :
Customer Reviews for Product and allied services has become a de-facto for Vendors selling products online. Customer reviews for a product is becoming more important day by day as e-commerce industry grows imminently. For a renowned product, the number of customer reviews can run to many counts. This makes the buying decision for the customer more complex. The crux of this research work is to do a summarization of all the customer reviews of a product. This summarization task calls out the specific feature details like opinions of the product unlike the conventional text summarization including positive and negative. No original sentences of reviews are summarized by selecting or rewriting to identify the important concepts as in the classic text summarization. The interest is limited to the mining of opinion and product features captured as part of the summarization task. This mining increases the land scape for the mine vector under analysis, to compare more product and rank the product based on the reviews instantly on own.
Keywords :
"Feature extraction","Blogs","Tagging","Search engines","Support vector machines","Semantics","Unsupervised learning"
Conference_Titel :
Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2015 International Conference on
DOI :
10.1109/ICCICCT.2015.7475277