On leveraging user access patterns for topic specific crawling

Abstract

In recent years, there has been considerable research on constructing crawlers which find resources satisfying specific conditions called predicates. Such a predicate could be a keyword query, a topical query, or some arbitrary contraint on the internal structure of the web page. Several techniques such as focussed crawling and intelligent crawling have recently been proposed for performing the topic specific resource discovery process. All these crawlers are linkage based, since they use the hyperlink behavior in order to perform resource discovery. Recent studies have shown that the topical correlations in hyperlinks are quite noisy and may not always show the consistency necessary for a reliable resource discovery process. In this paper, we will approach the problem of resource discovery from an entirely different perspective; we will mine the significant browsing patterns of world wide web users in order to model the likelihood of web pages belonging to a specified predicate. This user behavior can be mined from the freely available traces of large public domain proxies on the world wide web. For example, proxy caches such as Squid are hierarchical proxies which make their logs publically available. As we shall see in this paper, such traces are a rich source of information which can be mined in order to find the users that are most relevant to the topic of a given crawl. We refer to this technique as collaborative crawling because it mines the collective user experiences in order to find topical resources. Such a strategy turns out to be extremely effective because the topical consistency in world wide web browsing patterns turns out to very high compared to the noisy linkage information. In addition, the user-centered crawling system can be combined with linkage based systems to create an overall system which works more effectively than a system based purely on either user behavior or hyperlinks.