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Reseach Article

Identifying and Ranking Dominating Product Features using NLP Technique

by Sonali D. Ingale, Ratnadeep R. Deshmukh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 17
Year of Publication: 2015
Authors: Sonali D. Ingale, Ratnadeep R. Deshmukh

Sonali D. Ingale, Ratnadeep R. Deshmukh . Identifying and Ranking Dominating Product Features using NLP Technique. International Journal of Computer Applications. 122, 17 ( July 2015), 14-17. DOI=10.5120/21792-5135

@article{ 10.5120/21792-5135,
author = { Sonali D. Ingale, Ratnadeep R. Deshmukh },
title = { Identifying and Ranking Dominating Product Features using NLP Technique },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 17 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 14-17 },
numpages = {9},
url = { },
doi = { 10.5120/21792-5135 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:10:48.931755+05:30
%A Sonali D. Ingale
%A Ratnadeep R. Deshmukh
%T Identifying and Ranking Dominating Product Features using NLP Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 17
%P 14-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

As internet usage increased users uses internet not only to access and search information but also at the same time able to spread and publish own idea, sentiments, knowledge via different number of websites. Different websites encourage their user to write their views in the form of electronic text. This system increasing user-written electronic text in the world of internet, large numbers of user opinions are available on World Wide Web. User review contains important information, which is beneficial for customer as well as retailer. These reviews are in scattered format so extracting important data from this large corpus is time consuming work. Here developing a system which will automatically identify and rank the product features. The Stanford parser is used for identify product features. Sentence level sentiment classification is used for identify sentiment of each sentence separately, Sentiment Classifier is used for classifying each sentence, and finally a probabilistic ranking algorithm is used to rank the product features.

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Index Terms

Computer Science
Information Sciences


Sentiment classification Sentence level sentiment classification probabilistic aspect ranking.