Collaborative crawling: Mining user experiences for topical resource discovery

Abstract

The rapid growth of the world wide web had made the problem of topic specific resource discovery an important one in recent years. In this problem, it is desired to find web pages which satisfy a predicate specified by the user. Such a predicate could be a keyword query, a topical query, or some arbitrary constraint. Several techniques such as focused crawling and intelligent crawling have recently been proposed for topic specific resource discovery. 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. We refer to this technique as collaborative crawling because it mines the collective user experiences in order to find topical resources. Such a strategy is extremely effective because the topical consistency in world wide web browsing patterns turns out to very reliable. 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.