Bootstrapped Extraction of Class Attributes

Presented at: 18th International World Wide Web Conference (WWW2009)

by Joseph Reisinger, Marius Pasca

Webpage: http://www2009.eprints.org/198/1/p1235.pdf

As an alternative to previous studies on extracting class attributes from unstructured text, which consider either Web documents or query logs as the source of textual data, A bootstrapped method extracts class attributes simultaneously from both sources, using a small set of seed attributes. The method improves extraction precision and also improves attribute relevance across 40 test classes.

Keywords: Poster Session


Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2009/paper/198


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