OXPath: little language, little memory, great value

Andrew Jon Sellers, Tim Furche, Georg Gottlob, Giovanni Grasso, Christian Schallhart

Abstract: Data about everything is readily available on the web-but often only accessible through elaborate user interactions. For automated decision support, extracting that data is essential, but infeasible with existing heavy-weight data extraction systems. In this demonstration, we present OXPath, a novel approach to web extraction, with a system that supports informed job selection and integrates information from several different web sites. By carefully extending XPath, OXPath exploits its familiarity and provides a light-weight interface, which is easy to use and embed. We highlight how OXPath guarantees optimal page buffering, storing only a constant number of pages for non-recursive queries.