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ANALYSING PRODUCT REVIEWS USING DEEP-LEARNING MODEL

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dc.contributor.author Rai, Nitesh Kumar
dc.date.accessioned 2022-02-07T05:10:33Z
dc.date.available 2022-02-07T05:10:33Z
dc.date.issued 2019-05
dc.identifier.uri http://localhost:8081/xmlui/handle/123456789/15306
dc.description.abstract Due to explosive evolution and popularity of electronic media, Online shopping and Social media sites, vast amount of user review and experience available in the form of raw data. It can be used for opining mining or sentiment mining and other pattern identi cation tasks. Opining mining or sentiment mining and summerization of review regarding any particular topic used to provide insights and can be used as feedback to improve or address concerns regarding that topic and helpful in future planning. Most of the work done so far in this eld foced on run of the mill, well de ned techniques like K-NN, SVM and others machnine learning algorithms to classify the text into two or more classes. However, traditional techniques peak out, in term of accuracy in certain limit. Additional improvement in term of accuracy reported using deep learning model LSTM-RNN with pre-trained word embedding. The aim of the present work is to improve existing techniques for opinion mining or sentiment analysis. en_US
dc.description.sponsorship INDIAN INSTITUTE OF TECHNOLOGY ROORKEE en_US
dc.language.iso en en_US
dc.publisher I I T ROORKEE en_US
dc.subject Learning Model LSTM-RNN en_US
dc.subject Electronic Media en_US
dc.subject Opining Mining en_US
dc.subject Machine Learning Algorithms en_US
dc.title ANALYSING PRODUCT REVIEWS USING DEEP-LEARNING MODEL en_US
dc.type Other en_US


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