Publication Type

Conference Proceeding Article

Publication Date

10-2015

Abstract

Multipartite entity resolution seeks to match entity mentions across several collections. An entity mention is presumed unique within a collection, and thus could match at most one entity mention in each of the other collections. In addition to domain-specific features considered in entity resolution, there are a number of domain-invariant structural contraints that apply in this scenario, including one-to-one assignment as well as cross-collection transitivity. We propose a principled solution to the multipartite entity resolution problem, building on the foundation of Markov Logic Network (MLN) that combines probabilistic graphical model and first-order logic. We describe how the domain-invariant structural constraints could be expressed appropriately in terms of Markov logic, flexibly allowing joint modeling with domain-specific features. Experiments on two real-life datasets, each spanning four collections, show the utility of this approach and validate the contributions of various MLN components.

Keywords

entity resolution, markov logic network, structural constraints

Discipline

Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

CIKM 2015: Proceedings of the 24th ACM International Conference on Information and Knowledge Management, October 19-23, Melbourne

First Page

1691

Last Page

1694

ISBN

9781450337946

Identifier

10.1145/2806416.2806590

Publisher

ACM

City or Country

New York

Additional URL

http://dx.doi.org/10.1145/2806416.2806590

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