Rule-based word clustering for text classification

ABSTRACT

This paper introduces a rule-based, context-dependent word clustering method, with the rules derived from various domain databases and the word text orthographic properties. Besides significant dimensionality reduction, our experiments show that such rule-based word clustering improves by 8 the overall accuracy of extracting bibliographic fields from references, and by 18.32 on average the class-specific performance on the line classification of document headers.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

General Terms:
Algorithms

Keywords:
feature dimensionality reduction, word clustering