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dc.contributor.authorSharma, V.
dc.contributor.authorKhemnar, R.
dc.contributor.authorKumari, R.
dc.contributor.authorMohan, B.R.
dc.date.accessioned2020-03-30T09:46:11Z-
dc.date.available2020-03-30T09:46:11Z-
dc.date.issued2019
dc.identifier.citation2019 2nd International Conference on Intelligent Communication and Computational Techniques, ICCT 2019, 2019, Vol., , pp.178-181en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/6814-
dc.description.abstractStock price prediction has been a major area of research for many years. Accurate predictions can help investors take correct decisions about the selling/purchase of stocks. This paper aims to predict and gauge stock costs and patterns, utilizing the power of machine learning, content examination and fundamental analysis, to give traders a hands-on tool for keen speculations particularly for the volatile Indian Stock Market. We propose a technique to analyze and predict the stock price with the help of sentiment analysis and decomposable time series model along with multivariate-linear regression. � 2019 IEEE.en_US
dc.titleTime series with sentiment analysis for stock price predictionen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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