Learning Co-reference Relations for FOAF Instances

Abstract

FOAF is widely used on the Web to describe people, groups and organizations and their properties. Since FOAF does not require unique IDs, it is often unclear when two FOAF instances are co-referent, i.e., denote the same entity in the world. We describe a prototype system that identifies sets of co-referent FOAF instances using logical constraints (e.g., IFPs), strong heuristics (e.g., FOAF agents described in the same file are not co-referent), and a Support Vector Machine (SVM) generated classifier.