Mixed Based Classifier Approach for Sentiment Analysis

dc.contributor.authorBhatia, Sudhanhsu
dc.contributor.supervisorMishra, Ashutosh
dc.contributor.supervisorMiglani, Sumit
dc.date.accessioned2015-07-28T06:10:42Z
dc.date.available2015-07-28T06:10:42Z
dc.date.issued2015-07-28T06:10:42Z
dc.descriptionM.E. (Software Engineering)en
dc.description.abstractThe increasing expansion of social media stuff provides massive collection of textual information. People share their thoughts and views on the WEB. So sentiment analysis used to classifies the sentiments or the opinions from this huge amount of data. There are already many algorithms to find the sentiment form the data but there are many difficulties present to handle data like slang words and miss-spelling so the efficiency and the accuracy of these algorithms became poor. In this methodology the underlying idea is to achieve a particular accuracy rate by a new mixed algorithm by using different approaches like POS, N-Gram and some lexicon techniques.en
dc.description.sponsorshipComputer Science and Engineering, Thapar Univesity, Patialaen
dc.format.extent2338051 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10266/3425
dc.language.isoenen
dc.subjecttwitter APIen
dc.subjectGoogle APIen
dc.subjectSentiment Analysisen
dc.subjectMongo DBen
dc.subjectN-Gramen
dc.subjectComputer Scienceen
dc.subjectCSEDen
dc.titleMixed Based Classifier Approach for Sentiment Analysisen
dc.typeThesisen

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