WAM-Miner: in the search of web access motifs from historical web log data

Existing web usage mining techniques focus only on discovering knowledge based on the statistical measures obtained from the static characteristics of web usage data. They do not consider the dynamic nature of web usage data. In this paper, we focus on discovering novel knowledge by analyzing the change patterns of historical web access sequence data. We present an algorithm called Wam-Miner to discover Web Access Motifs (WAMs). WAMs are web access patterns that never change or do not change significantly most of the time (if not always) in terms of their support values during a specific time period. WAMs are useful for many applications, such as intelligent web advertisement, web site restructuring, business intelligence, and intelligent web caching. Categories and Subject Descriptors: H.2.8 [Database Management]: Database Applications – Data Mining. General Terms: Algorithm, Design, Experimentation.

• Type: Conference
• Year: 2005
• Where: CIKM
• Authors: Qiankun Zhao, Sourav S. Bhowmick, Le Gruenwald
• Keywords: CIKM 2005, Web Access, Web Usage Data, Web Usage Mining