Investigation of E-Commerce based User’s Traversal Path Patterns using MFB and MBP
Abstract
Web mining can be connected to discover user traversal path patterns that can be broke down to enhance traversability and structure of a website. It uncovers the data that how the web pages are become to and what the web clients are looking for. The web log server stores users’ behavioural navigational pattern and it is the hotspot for traversal design inventions. In this paper we investigate the e-commerce based Traversal Path Patterns and purchasing behaviour using data mining technique, here we analyses two types of traversal patterns i.e Maximal Forward Path and Maximal Backward Path. A Maximal forward path is defined as the longest consecutive sequence of forward references before the first backward reference is made to visit some previously visited page in the same session. Where documents are interconnected together to enable collaborating access in e-commerce website design which is prime and significant concern for successful business certainly users traceability and accessibility made easy.
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