Bootstrapped Extraction of Class Attributes

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

by Joseph Reisinger, Marius Pasca


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

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