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  • 标题:Customer Behavior Forecasting Using Big Data Analytics
  • 本地全文:下载
  • 作者:M P Geetha ; B Darshini ; M Karthikeyan
  • 期刊名称:International Journal of Advances in Engineering and Management
  • 电子版ISSN:2395-5252
  • 出版年度:2021
  • 卷号:3
  • 期号:3
  • 页码:370-377
  • DOI:10.35629/5252-0303230237
  • 语种:English
  • 出版社:IJAEM JOURNAL
  • 摘要:From an enormous dataset to enhance the accuracy and efficiency of forecasting the Data mining techniques are the very effective tools in extracting the hidden knowledge. Intelligent Decision Analytical System needs integration of decision analysis and predictions. The accuracy in sales forecast provides a huge impact in business. Many of the business organizations are mostly depend on a knowledge base and demand prediction of sales trends. The detailed study and analysis of comprehensible predictive models to improve the future sales predictions are to be carried out in this proposed work. These problems could be overcome by using various data mining techniques. The concept of sales data and sales forecast is briefly analyzed, in this project. The various techniques and measures for the sales predictions are identified. On the basis of a performance evaluation, an apt predictive model is suggested for the sales trend forecast.
  • 关键词:consumer behaviour;data analytics;random forest;linear regression;sales prediction
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