Bootstrapped extraction of class attributes

ABSTRACT

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.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing

General Terms:
Algorithms, Experimentation

Keywords:
attribute extraction