Discovering More Accurate Frequent Web Usage Patterns

TL;DR

This paper introduces a new method for discovering more accurate frequent web usage patterns by improving session reconstruction and pattern discovery, validated using a web user behavior simulator.

Contribution

It proposes a novel approach for web usage pattern discovery that enhances accuracy after session reconstruction, using a web user behavior simulation for validation.

Findings

Improved pattern discovery accuracy demonstrated with simulation data.

Session reconstruction quality significantly impacts pattern discovery results.

The method outperforms existing techniques in accuracy.

Abstract

Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web users. As in classical data mining, data preparation and pattern discovery are the main issues in web usage mining. The first phase of web usage mining is the data processing phase, which includes the session reconstruction operation from server logs. Session reconstruction success directly affects the quality of the frequent patterns discovered in the next phase. In reactive web usage mining techniques, the source data is web server logs and the topology of the web pages served by the web server domain. Other kinds of information collected during the interactive browsing of web site by user, such as cookies or web logs containing similar information, are not used. The next phase of web usage mining is discovering frequent user navigation patterns. In this phase, pattern discovery methods are applied on the reconstructed sessions obtained in the first phase in order to discover frequent user patterns. In this paper, we propose a frequent web usage pattern discovery method that can be applied after session reconstruction phase. In order to compare accuracy performance of session reconstruction phase and pattern discovery phase, we have used an agent simulator, which models behavior of web users and generates web user navigation as well as the log data kept by the web server.