Mining Web navigation patterns with a path traversal graph
Journal
Expert Systems with Applications
Journal Volume
38
Journal Issue
6
Pages
7112-7122
Date Issued
2011
Author(s)
Wang Y.-T.
Abstract
Understanding the navigational behaviour of website visitors is a significant factor of success in the emerging business models of electronic commerce and even mobile commerce. However, Web traversal patterns obtained by traditional Web usage mining approaches are ineffective for the content management of websites. They do not provide the big picture of the intentions of the visitors. The Web navigation patterns, termed throughout-surfing patterns (TSPs) as defined in this paper, are a superset of Web traversal patterns that effectively display the trends toward the next visited Web pages in a browsing session. TSPs are more expressive for understanding the purposes of website visitors. In this paper, we first introduce the concept of throughout-surfing patterns and then present an efficient method for mining the patterns. We propose a compact graph structure, termed a path traversal graph, to record information about the navigation paths of website visitors. The graph contains the frequent surfing paths that are required for mining TSPs. In addition, we devised a graph traverse algorithm based on the proposed graph structure to discover the TSPs. The experimental results show the proposed mining method is highly efficient to discover TSPs. ? 2010 Elsevier Ltd. All rights reserved.
Subjects
Browsing behaviour
Path traversal graph
Throughout-surfing pattern
Web log mining
Web traversal pattern
Type
journal article