Title :
An approach towards feature specific opinion mining and sentimental analysis across e-commerce websites
Author :
Kumar Singh, Prashast ; Sachdeva, Anish ; Mahajan, Dhruv ; Pande, Nishtha ; Sharma, Ashok
Author_Institution :
CSE Dept., MSIT, New Delhi, India
Abstract :
This research aims to automate the process of gathering online, end user reviews for any given product or service and analyzing those reviews in terms of the sentiments expressed about specific features. This involves the filtering of irrelevant and unhelpful reviews, quantification of the sentiments of thousands of (useful) reviews. And finally, providing the end user (business/manufacturer) summarized data about the expressed sentiments in way of intuitive and easy to understand graphs, charts and other visualization. This data can then be used to improve business outcomes and ensure a very high level of customer satisfaction.
Keywords :
Web sites; customer satisfaction; data mining; data visualisation; electronic commerce; information filtering; text analysis; business outcome; charts; customer satisfaction; e-commerce Websites; end user summarized data; feature specific opinion mining; graphs; irrelevant review filtering; online end user review gathering; product review; review analysis; sentiment quantification; sentimental analysis; service review; unhelpful review filtering; visualization; Batteries; Business; Data mining; Databases; Feature extraction; Filtering; Knowledge based systems; Opinion mining; Sentiment Analysis; ecommerce; feature specific mining;
Conference_Titel :
Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -
Conference_Location :
Noida
Print_ISBN :
978-1-4799-4237-4
DOI :
10.1109/CONFLUENCE.2014.6949312
