Comparison of interestingness functions for learning web usage patterns Xiangji Huang, Nick Cercone, and Aijun An   View Paper (PDF)   Return to Industry session 2: data mining and federated systems Abstract Livelink is a collaborative intranet, extranet and e-business application that enables employees and business partners of an organization to capture, share and reuse business information and knowledge. The usage of the Livelink software has been recorded by the Livelink Web server in its log files. We present an application of data mining techniques to the Livelink Web usage data. In particular, we focus on how to find interesting association rules and sequential patterns from the Livelink log files. A number of interestingness measures are used in our application to identify interesting rules and patterns. We present a comparison of these measures based on the feedback from domain experts. Some of the interestingness measures are found to be better than others. DiSC'03 © 2003 Association for Computing Machinery