Publication Type
Conference Proceeding Article
Version
publishedVersion
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
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
Citation
YE, Tengyuan and LAUW, Hady W..
Structural Constraints for Multipartite Entity Resolution with Markov Logic Network. (2015). CIKM 2015: Proceedings of the 24th ACM International Conference on Information and Knowledge Management, October 19-23, Melbourne. 1691-1694.
Available at: https://ink.library.smu.edu.sg/sis_research/2890
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2806416.2806590