First-Order learning for web mining

Abstract

We present compelling evidence that the World Wide Web is a domain in which applications can benefit from using first-order learning methods, since the graph structure inherent in hypertext naturally lends itself to a relational representation. We demonstrate strong advantages for two applications - learning classifiers for Web pages, and learning rules to discover relations among pages.