DocumentCode :
2556895
Title :
Opinion mining from user reviews
Author :
Tripathy, Amiya Kumar ; Sundararajan, Revathy ; Deshpande, Chinmay ; Mishra, Pankaj ; Natarajan, Neha
Author_Institution :
Dept. of Comput. Eng., Don Bosco Inst. of Technol., Mumbai, India
fYear :
2015
fDate :
4-6 Feb. 2015
Firstpage :
1
Lastpage :
5
Abstract :
Due to advancement of technology and mainly Internet, the concept of marketing and selling of product has reached to a new level. Now-a-days, lots of companies rely on user reviews for launching their product. These reviews play an important role or companies to know how their product has been accepted in the market. But, today, thousands of reviews are generated for a product. Companies have to process each of these reviews to get user opinion as well as ideas, which is a very tedious and time-consuming. This paper discourses about extracting opinions from the user reviews is semi-automatic, in the sense that it requires some amount of expert assistance. Expert assistance is required for building the domain knowledge for the system, so as to make the system learn about the domain specific words]. The proposed system, using domain knowledge, identifies and extracts the opinions for a given product. These extracted opinions include the opinion words, their polarity in from of weights and for which feature these opinions was provided and system aggregates the extracted opinions them for better display.
Keywords :
data mining; marketing data processing; Internet; expert assistance; marketing concept; opinion mining; product selling; user review; Companies; Data mining; Feature extraction; Hidden Markov models; Mobile communication; Sentiment analysis; Sustainable development; data extraction; data mining; hidden Markov model; opinion extraction; opinion mining; sentiment analysis; user reviews;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technologies for Sustainable Development (ICTSD), 2015 International Conference on
Conference_Location :
Mumbai
Type :
conf
DOI :
10.1109/ICTSD.2015.7095904
Filename :
7095904
Link To Document :
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