Structural Constraints for Multipartite Entity Resolution with Markov Logic Network
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 resolutio...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2015
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/2890 https://ink.library.smu.edu.sg/context/sis_research/article/3890/viewcontent/cikm15.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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