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  Published Paper Details:

  Paper Title

BIG DATA AND NEURAL NETWORK APPROACH ON ONLINE PRODUCT SALES PREDICTION USING CUSTOMER REVIEWS AND PROMOTION STRATAGEM - A REVIEW

  Authors

  G. Midhu Bala,  Dr. K. Chitra

  Keywords

Web scraping, Neural Network, Locating files in websites, online sale promotion strategies.

  Abstract


With the advent of Information Technology (IT) and Data Sciences, businesses now have the opportunity to better understand and forecast consumer demands using quantitative methods. The use of Big Data to better understand business processes and results is an evolving IT trend that has piqued the interest of researchers and practitioners. Big Data systems have the potential to assist businesses in better understanding complicated business relationships by delivering knowledge that was previously unavailable. Previous research has shown that providing an effective supply chain gives a producer a competitive advantage over its competitors, how data from online marketplaces or e-commerce allows manufacturers to better understand product demands is a field that has not been thoroughly researched by previous researchers. This paper provides a comprehensive survey about the ongoing researches done in this field by reviewing the articles of the other computer scientists. This paper paves a better way for the upcoming researchers in this field.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2106387

  Paper ID - 208301

  Page Number(s) - d416-d420

  Pubished in - Volume 9 | Issue 6 | June 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  G. Midhu Bala,  Dr. K. Chitra,   "BIG DATA AND NEURAL NETWORK APPROACH ON ONLINE PRODUCT SALES PREDICTION USING CUSTOMER REVIEWS AND PROMOTION STRATAGEM - A REVIEW", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 6, pp.d416-d420, June 2021, Available at :http://www.ijcrt.org/papers/IJCRT2106387.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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