Data Mining of Web Access Logs
Anand S. Lalani · 2003
Analysis of web visitors access patterns can lead to benefits in a wide range of areas such as decision support and website restructuring. Data mining techniques can be used to find access patterns hidden inside huge volumes of web access data. The goal of this thesis is to determine whether there are any such patterns in the web access data for the computer science website of RMIT university. In particular, this thesis investigates whether there are any differences in access patterns between: (1) Visitors from within Australia and visitors from outside Australia. (2) Visitors from within RMIT university and visitors from outside RMIT university. (3) Visitors from within RMIT university and visitors from outside RMIT university but within Australia. (4) Visitors from educational institutions other than RMIT university and visitors from non-educational institutions. The data mining techniques of classification, association rules, clustering and attribute selection were used with four different feature sets. The entire pattern discovery process was divided into three major steps: (1) Transaction identification and feature extraction (2) Discovery of the access patterns. (3) Analysis of the discovered patterns for their