Paper: Profile Based Cross-Document Coreference Using Kernelized Fuzzy Relational Clustering

ACL ID P09-1047
Title Profile Based Cross-Document Coreference Using Kernelized Fuzzy Relational Clustering
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Coreferencing entities across documents in a large corpus enables advanced document understanding tasks such as question answering. This paper presents a novel cross document coreference approach that leverages the profiles of entities which are constructed by using information extraction tools and reconciled by using a within-document coreference module. We propose to match the profiles by using a learned ensemble distance function comprised of a suite of similarity specialists. We develop a kernelized soft relational clustering algorithm that makes use of the learned distance function to partition the entities into fuzzy sets of identities. We compare the kernelized clustering method with a popular fuzzy relation clustering algorithm (FRC) and show 5% improvement in coreference performan...