Product Score Based on Preferential Treatment of Aspects and Sentiment Classification

Authors(4) :-K. N. Karthikheyan, D. Kamesh, S. Pradeep Kumar, Dr. N. Pughazendi

Every user has a varying perception on a same product. An attribute that entices one, may be a turn-off to the other. For instance, a traveller may fancy the attribute “battery” on a mobile phone while a person who seeks a “slimmest mobile” may abhor its size enlargement caused by the same battery. This project aspires to display the consumer with the product possessing the attribute that appeals the consumer, whose search results are based on the reviews posted by the numerous users of the product around the world on different websites. The rapidly expanding e-commerce has facilitated consumers to purchase products online. More than $156 million online product retail sales have been done in the US market during 2009 . Most retail Web sites encourage consumers to write reviews to express their opinions on various aspects of the products. This gives rise to huge collections of consumer reviews on the Web. These reviews have become an important resource for both consumers and ?rms. Consumers commonly seek quality information from online consumer reviews prior to purchasing a product, while many ?rms use online consumer reviews as an important resource in their product development, marketing, and consumer relationship management. As illustrated in this figure most online reviews express consumers’ overall opinion ratings on the product, and their opinions on multiple aspects of the product. While a product may have hundreds of aspects, we argue that some aspects are more important than the others and have greater in?uence on consumers’ purchase decisions as well as ?rms’ product development strategies. Take iPhone 3GS as an example, some aspects like “battery” and “speed,” are more important than the others like “moisture sensor.” Generally, identifying the important product aspects will bene?t both consumers and ?rms. Consumers can conveniently make wise purchase decision by paying attentions on the important aspects, while ?rms can focus on improving the quality of these aspects and thus enhance the product reputation effectively.

Authors and Affiliations

K. N. Karthikheyan
Computer Science and Engineering, Panimalar Engineering College, Chennai, India
D. Kamesh
Computer Science and Engineering, Panimalar Engineering College, Chennai, India
S. Pradeep Kumar
Computer Science and Engineering, Panimalar Engineering College, Chennai, India
Dr. N. Pughazendi
Computer Science and Engineering, Panimalar Engineering College, Chennai, India

Aspect ranking, product score, priority ranking

Publication Details

Published in : Volume 1 | Issue 2 | March-April 2015
Date of Publication : 2015-04-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 289-294
Manuscript Number : IJSRSET152283
Publisher : Technoscience Academy

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

Cite This Article :

K. N. Karthikheyan, D. Kamesh, S. Pradeep Kumar, Dr. N. Pughazendi, " Product Score Based on Preferential Treatment of Aspects and Sentiment Classification, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 2, pp.289-294, March-April-2015.
Journal URL : http://ijsrset.com/IJSRSET152283

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