Publication | Closed Access
Entity Matching across Heterogeneous Sources
33
Citations
30
References
2015
Year
Unknown Venue
Target DomainEngineeringSource DomainSemantic WebCorpus LinguisticsText MiningNatural Language ProcessingEntity MatchingInformation RetrievalData ScienceComputational LinguisticsManagementData IntegrationNamed-entity RecognitionData ManagementHeterogeneous Database SystemMatching TechniqueEntity DisambiguationKnowledge DiscoveryEast Asian LanguagesTerminology ExtractionComputer ScienceSource EntityKeyword ExtractionData HeterogeneityData Modeling
Given an entity in a source domain, finding its matched entities from another (target) domain is an important task in many applications. Traditionally, the problem was usually addressed by first extracting major keywords corresponding to the source entity and then query relevant entities from the target domain using those keywords. However, the method would inevitably fails if the two domains have less or no overlapping in the content. An extreme case is that the source domain is in English and the target domain is in Chinese.
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