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dc.contributor.authorHassell, Joseph Edward
dc.description.abstractPrecisely identifying entities in web documents is essential for document indexing, web search and data integration. Entity disambiguation is the challenge of determining the correct entity out of various candidate entities. Our novel method utilizes background knowledge in the form of a populated ontology. Additionally, it does not rely on the existence of any structure in a document or the appearance of data items that can provide strong evidence, such as e-mail addresses, for disambiguating authors for example. Originality of our method is demonstrated in the way it uses different relationships in a document as well as in the ontology to provide clues in determining the correct entity. We demonstrate the applicability of our method by disambiguating authors in a collection of DBWorld posts using a large scale, real-world ontology extracted from the DBLP. The precision and recall measurements provide encouraging results.
dc.subjectEntity disambiguation
dc.subjectsemantic web.
dc.titleOntology-driven automatic entity disambiguation in unstructured text
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorBudak Arpinar
dc.description.committeeBudak Arpinar
dc.description.committeeJohn Miller
dc.description.committeeAmit Sheth

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