This paper is published in Volume-4, Issue-1, 2018
Area
Computer Engineering
Author
Prajakta Ghavare, Prashant Ahire
Org/Univ
Dr. D.Y. Patil College of Engineering, Pune, Maharashtra, India
Pub. Date
08 January, 2018
Paper ID
V4I1-1172
Publisher
Keywords
Data Mining, E-commerce, Web Logs Analysis, Behavioral Patterns, Model Checking.

Citationsacebook

IEEE
Prajakta Ghavare, Prashant Ahire. Big Data Classification of Users Navigation and Behavior Using Web Server Logs, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Prajakta Ghavare, Prashant Ahire (2018). Big Data Classification of Users Navigation and Behavior Using Web Server Logs. International Journal of Advance Research, Ideas and Innovations in Technology, 4(1) www.IJARIIT.com.

MLA
Prajakta Ghavare, Prashant Ahire. "Big Data Classification of Users Navigation and Behavior Using Web Server Logs." International Journal of Advance Research, Ideas and Innovations in Technology 4.1 (2018). www.IJARIIT.com.

Abstract

Users for online shopping are increasing day by day because of easy to get and time-saving property of online shopping. Having a proper understanding of users interest for certain type of product or different products for online shopping becomes important to create personalized service for a target market. An important property of successful e-commerce website is the ability to provide useful content at the right time to users. And because of all this, personalization techniques are introduced to create adaptive shopping application in which user interfaces change according to users interest. User’s behavior information is stored in web log files, and to get the information data mining techniques are used in which they use statistical characters to model users behavior and not considering the sequence of action performed by uses. It becomes helpful if we follow user’s session to understand complex user behavior. Therefore to eliminates all these issues this paper proposes a linear-temporal logic model checking approach for the analysis of structured e-commerce weblogs. If we consider a common way of mapping log records according to e-commerce structure, weblogs can be easily converted into event logs by which behavior of the user is captured. After getting users behavior by performing different predefine queries to identify different behavioral patterns that consider the different actions performed by a user during a session.