Mining Web Access Logs of an On-line Newspaper
Paulo Jorge dos Mártires Batista, Mário J. Silva · 2002
With the explosive growth of data available on the Internet, personalization of this information space become a necessity. An important component of web personalization is the automatic knowledge extraction from web log files. However, analysis of large web log files is a complex task not fully addressed by existing web access analyzers. Using commercial software, we applied well-known data mining techniques (association rules and clustering) to analyze access log records collected on a web newspaper. This paper identifies several reading patterns and discusses approaches for mining this data.