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HOMS: Hindi Opinion Mining System

Jha, Vandana and Manjunath, N and Shenoy, Deepa P and Venugopal, KR and Patnaik, LM (2015) HOMS: Hindi Opinion Mining System. In: IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS), JUL 09-11, 2015, Jadavpur Univ, Kolkata, INDIA, pp. 366-371.

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Official URL: http://dx.doi.org/10.1109/ReTIS.2015.7232906


With the increasing popularity of the Web 2.0, we are provided with more documents which express opinions on different issues. Online posting reviews has become an increasingly preferred way for people to express opinions and sentiments towards the products bought/used or services received. Analysing the large volume of online review data available, would produce useful knowledge, which could be of economic values to vendors and other interested parties. A lot of work in Opinion Mining exists for English language. In the last few years, web contents are increasing in other languages also at a faster rate and hence there is a requirement to execute opinion mining in other languages. In this paper, a Hindi Opinion Mining System (HOMS) is proposed for movie review data. It performs the task of opinion mining at the document level and classifies the documents as positive, negative and neutral using two different methods: Machine learning technique and Part-Of-Speech (POS) tagging. We have used Naive Bayes Classifier for Machine learning and in POS tagging, we have considered adjectives as opinion words. Extensive simulations conducted on a large movie data set confirms the effectiveness of the proposed approach.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited: 25 Aug 2016 10:10
Last Modified: 25 Aug 2016 10:10
URI: http://eprints.iisc.ac.in/id/eprint/54545

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