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dc.contributor.authorPereira, Bianca
dc.identifier.citationPereira, B. (2014). Entity Linking with Multiple Knowledge Bases: An Ontology Modularization Approach. In P. Mika, T. Tudorache, A. Bernstein, C. Welty, C. Knoblock, D. Vrandecic, P. Groth, N. Noy, K. Janowicz, C. Goble & B. Pereira (Eds.), The Semantic Web - ISWC 2014 (Vol. 8797, pp. 513-520): Springer International Publishing.en_US
dc.descriptionConference paperen_US
dc.description.abstractThe recognition of entities in text is the basis for a series of applications. Synonymy and Ambiguity are among the biggest challenges in identifying such entities. Both challenges are addressed by Entity Linking, the task of grounding entity mentions in textual documents to Knowledge Base entries. Entity Linking has been based in the use of single cross-domain Knowledge Bases as source for entities. This PhD research proposes the use of multiple Knowledge Bases for Entity Linking as a way to increase the number of entities recognized in text. The problem of Entity Linking with Multiple Knowledge Bases is addressed by using textual and Knowledge Base features as contexts for Entity Linking, Ontology Modularization to select the most relevant subset of entity entries, and Collective Inference to decide the most suitable entity entry to link with each mention.en_US
dc.relation.ispartofseriesLecture Notes in Computer Science;8797
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.subjectEntity Linkingen_US
dc.subjectLinked dataen_US
dc.subjectOntology modularizationen_US
dc.titleEntity Linking with Multiple Knowledge Bases: An Ontology Modularization Approachen_US
dc.typeConference Paperen_US

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Attribution-NonCommercial-NoDerivs 3.0 Ireland
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland