Multiple Product Aspect Ranking using Sentiment Classification

Authors(4) :-Ms. Sangeetha C. K, Ms. MohanaPriya V, Ms. Rashmika S, Mrs. Abirami G

Consumers normally seek tone information from online reviews prior purchasing a product, while many business firms use online customer reviews as significant feedbacks in developing, marketing and promoting their product. The objective of our work is proposing a product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at making it easier for the consumers in buying the product by using the numerous online consumer reviews. Millions of reviews from various websites are clustered and made visible within each website by means of graphical representations of each aspect of different products. Therefore, our approach gives way to an iterative visual investigation and allows fast analysis of online consumer reviews.

Authors and Affiliations

Ms. Sangeetha C. K
Department of Information Technology, Dhanalakshmi College of Engineering, Chennai, Tamil Nadu, India.
Ms. MohanaPriya V
Department of Information Technology, Dhanalakshmi College of Engineering, Chennai, Tamil Nadu, India.
Ms. Rashmika S
Department of Information Technology, Dhanalakshmi College of Engineering, Chennai, Tamil Nadu, India.
Mrs. Abirami G
Department of Information Technology, Dhanalakshmi College of Engineering, Chennai, Tamil Nadu, India.

Aspect rating, aspect recognition, consumer reviews, opinions, product aspects, sentient assortment, graphical representation

Publication Details

Published in : Volume 1 | Issue 1 | January-February 2015
Date of Publication : 2015-02-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 165-169
Manuscript Number : IJSRSET151137
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Ms. Sangeetha C. K, Ms. MohanaPriya V, Ms. Rashmika S, Mrs. Abirami G, " Multiple Product Aspect Ranking using Sentiment Classification, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.165-169, January-February-2015. Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET151137

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