Pattern Discovery Using Association Rule Mining on Clustered Data

Htun Zaw Oo, Nang Saing Moon Kham

Many organizations use Word Wide Web as a multipurpose platform during these days. It is very important to understand how a website is being used by users. Web Usage Mining is the one of the data mining technique that aims to discover interesting usage patterns from web log data. It also helps effective website management, creating adaptive websites, personalization and so on. In this paper, the aim is to find frequent user access pattern from web log entries. Combined effort of clustering and association rule mining is used to apply for pattern discovery.