Finding Neighbor Communities in the Web Using Inter-site Graph

Abstract

In recent years, link-based information retrieval methods from the Web are developed. A framework of these methods is a Web graph using pages as vertices and Web-links as edges. In the last year, the authors have claimed that an inter-site graph using sites as vertices and global-links (links between sites) as edges is more natural and useful as a framework for link-based information retrieval than a Web graph. They have proposed directory-based sites as a new model of Web sites and established a method of identifying them from URL and Web-link data. They have examined that this method can identify directory-based sites almost correctly by using data of URLs and links in .jp domain. In this paper, we show that this framework is also useful for information retrieval in response to user’s query. We develop a system called Neighbor Community Finder (NCF, for short). NCF finds Web communities related to given URLs by constructing an inter-site graph with neighborhood sites and links obtained from the real Web on demand. We show that in several cases NCF is a more effective tool for finding related pages than Google’s service by computational experiments.