Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks
- Title
- Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks
- Creator
- David Winster Praveenraj D.; Prabha T.; Kalyan Ram M.; Muthusundari S.; Madeswaran A.
- Description
- The exponential development of e-commerce in recent decades has enhanced convenience for individuals. Compared to the conventional business environment, e-commerce is characterized by increased dynamism and complexity, resulting in several obstacles. Data mining assists individuals in effectively addressing these difficulties. Traditional data mining cannot efficiently use big data in the power provider industry. It heavily relies on time-consuming and labor-intensive feature engineering, and the resulting model could be more easily scalable. Convolutional Neural Networks (CNN) can efficiently use vast amounts of data and autonomously extract valuable elements from the original input, resulting in increased effectiveness. This article utilizes a CNN to extract valuable insights from e-commerce information to forecast commodities sales accurately and proposes a CNN-based Sales Forecasting Model (CNN-SFM). The findings indicate that using data mining and CNN yields a high level of precision in forecasting forthcoming people buying capacity data. The correlation variable between actual usage information and projected usage information was 0.98, and the highest mean error was just 1.78%. Data mining can effectively extract hidden relevant information and forecast future consumption habits for e-commerce systems. CNN demonstrates proficiency in accurately predicting forthcoming consumption power and trends. The Research Publication.
- Source
- Indian Journal of Information Sources and Services, Vol-14, No. 2, pp. 139-145.
- Date
- 2024-01-01
- Publisher
- The Research Publication
- Subject
- Convolutional Neural Networks; Data Mining; E-commerce; Sales Forecasting
- Coverage
- David Winster Praveenraj D., School of Business and Management, Christ University, Bangalore, India; Prabha T., Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India; Kalyan Ram M., Department of Computer Science and Engineering, Aditya Engineering College, Surampalem, India; Muthusundari S., Department of Computer Science and Engineering, R.M.D. Engineering College, Kavaraipettai, India; Madeswaran A., Department of School of Business Management, Christ University, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 22316094
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
David Winster Praveenraj D.; Prabha T.; Kalyan Ram M.; Muthusundari S.; Madeswaran A., “Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13216.