Preprint version. Published in Workshop on Web Information Management (WIDM) Proceedings: Bremen, Germany, November 1, 2005, pages 59-66.
Copyright © ACM 2005. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Workshop on Web Information Management (WIDM) Proceedings.
NOTE: At the time of publication, the author Alex Dekhtyar was not yet affiliated with Cal Poly.
In this paper we give a preliminary report on our study of the use of web server traffic logs to improve local search. Web server traffic logs are, typically, private to individual websites and as such – are unavailable to traditional web search engines conducting searches across multiple web sites. However, they can be used to augment search performed by a local search engine, restricted to a single site.
Web server traffic logs, which we will refer to as simply logs throughout this paper, contain information on traffic patterns on a web site. By using this information, instead of pure link counts in the computation of PageRank, we can obtain a new local measure of web site importance, based on frequency of visits to a page, rather than simply on the amount of links.
In this paper we describe the architecture of a search engine we have built for the Eastern Kentucky University (EKU) website and some preliminary experiments we have conducted with it.