Selection of Multi-Agent Model in e-Commerce using Data-Mining/Machine Learning

  • Dr. Dinesh Kumar Singh
  • Dr. Mohd Ashraf
  • Dr. R. K. Srivastava


The field of data mining is very big and there is several research areas are embedded with this field. The multi agent integration with data mining may help to provide many innovative solutions and helps information technology to provide the pattern for recommendation of web extraction data using many data mining algorithms. Themulti agent model diagnose on many problems. The main benefit of using multi agent and data mining is that they can combine use the deep learning and artificial intelligence. Using such systems helps to store the data sets for further study and the AI helps to provide the better solution of any problem. By every six month the ecommerce industry is taking new shape. New techniques and methodologies of sales and customer handling is introducing by every year. The commerce models are divided into three categories. In first category the small business interacts with big business known as B2B eCommerce. The second category deals with business to customer known as B2C eCommerce. The third category known as C2C ecommerce deals with customer to another customer business relations. The multi agent keeps tracks for such applications and using machine learning provides an mModel for the advancement of business and techniques. In this research such methods are studied.

How to Cite
Singh, D. D. K., Ashraf, D. M., & Srivastava, D. R. K. (2019). Selection of Multi-Agent Model in e-Commerce using Data-Mining/Machine Learning. International Journal of Control and Automation, 12(4), 110 - 114. Retrieved from