Abstract

The Semantic Web initiative puts emphasis not primarily on putting data on the Web, but rather on creating links in a way that both humans and machines can explore the Web of data. When such users access the Web, they leave a trail as Web servers maintain a history of requests. Web usage mining approaches have been studied since the begin-ning of the Web given the log’s huge potential for purposes such as resource annotation, personalization, forecasting etc. However, the impact of any such efforts has not really gone beyond generating statistics detailing who, when, and how Web pages maintained by a Web server were visited. In this paper, we propose a different approach of how to mine Web server logs by combining link analysis and usage analysis for events based on time-windowed views over usage logs. We detail our observations and argue that the sum of all Web Travel Footprints ’ data on the visitors access paths and the linkage of the resources within the site at a particu-lar time window gives sufficient insights at what constitutes relevance. Our findings are substantiated by presenting ev-idence in the form of exploratory graphics. 1.