Tracking of user's behaviour in Structured e-commerce Website

Author(s):

Chandana M , Sapthagiri college of engineering; Gajendra Prasad KC, Sapthagiri college of engineering; Komal Kumari, Sapthagiri college of engineering; Madduri Uma, Sapthagiri college of engineering; Smriti Gupta, Sapthagiri college of engineering

Keywords:

Data Mining, E-Commerce, Web Logs Analysis, behavioural Patterns, Model Checking

Abstract:

Online shopping is becoming more and more common in our daily lives. Tracking user’s interests and behaviour is essential in order to fulfil customer’s requirements. The information about user’s behaviour is stored in the web server logs. Absorbing a view of the process followed by user’s during a session can be of great interest to identify the behavioural patterns. The analysis of such information has focused on applying data mining techniques. Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. It is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs. To address this issue, this paper proposes a linear temporal logic model checking method for the analysis of structured e-commerce web logs. By defining a common way of tracing log records according to the ecommerce structure, web logs can be converted into event logs where the behaviour of user’s is tracked. Then, different predefined queries can be performed to identify different actions performed by a user during a session. The proposed approach has been studied by applying it to a real case study of a Spanish e-commerce website. The results have identified interesting findings that have made possible to propose some improvements in the website design with the aim of increasing its efficiency.

Other Details:

Manuscript Id	:	IJSTEV5I8004
Published in	:	Volume : 5, Issue : 8
Publication Date	:	01/03/2019
Page(s)	:	4-7

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