Usage Data for Predicting User Trends and Behavioral Analysis in E-Commerce Applications

Sathiyamoorthi V., T. Nadana Ravishankar, Ilavarasi A. K., Sridhar Udayakumar, Karthikeyan Harimoorthy, Jayapandian N. and Saravanan V.
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Sathiyamoorthi V.: Sona College of Technology, India
T. Nadana Ravishankar: Veltech Hightech Dr. Rangarajan Dr. Sakunthala Engineering College, India
Ilavarasi A. K.: Centre for Healthcare Advancement, Innovation and Research, Vellore Institute of Technology, Chennai, India
Sridhar Udayakumar: Mettu University, Ethiopia
Karthikeyan Harimoorthy: CHRIST University (Deemed), India
Jayapandian N.: Christ University (Deemed), India
Saravanan V.: Dambi Dollo University, Ethiopia

International Journal of Information Systems in the Service Sector (IJISSS), 2021, vol. 13, issue 4, 40-61

Abstract: Reviewing and buying the right goods from online websites is growing day by day in today's fast internet environment. Numerous goods in the same label are available to consumers. It is thus a difficult job for consumers to pick up the correct commodity at a decent price under different market conditions. Therefore, it is important for owners of online shopping websites to better understand their customers' needs and offer better services. For these reasons, the access log documented a vast amount of data related to user interactions with the websites. This access log therefore plays a key role in predicting user access trends and in recommending the best product to consumers. This research work therefore focuses on one such methodology for evaluating the pattern and behavioral analysis of users in e-commerce websites.

Date: 2021
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