2003 KernelMethodsForRelationExtraction

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Subject Headings: Relation Mention Recognition Algorithm, Relational Data Kernel Function


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We present an application of kernel methods to extracting relations from unstructured natural language sources. We introduce kernels defined over shallow parse representations of text, and design efficient algorithms for computing the kernels. We use the devised kernels in conjunction with Support Vector Machine and Voted Perceptron learning algorithms for the task of extracting person-affiliation and organization-location relations from text. We experimentally evaluate the proposed methods and compare them with feature-based learning algorithms, with promising results.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2003 KernelMethodsForRelationExtractionDmitry Zelenko
Chinatsu Aone
Anthony Richardella
Kernel Methods for Relation ExtractionThe Journal of Machine Learning Researchhttp://www.jmlr.org/papers/volume3/zelenko03a/zelenko03a.pdf2003