First-order learning for Web mining

It is presented 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.

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.