A Hybrid Approach for the Acquisition of Information Extraction Patterns

Mihai Surdeanu, Jordi Turmo, Alicia Ageno

Research output: Contribution to conferencePaperpeer-review

17 Scopus citations

Abstract

In this paper we present a hybrid approach for the acquisition of syntacticosemantic patterns from raw text. Our approach co-trains a decision list learner whose feature space covers the set of all syntactico-semantic patterns with an Expectation Maximization clustering algorithm that uses the text words as attributes. We show that the combination of the two methods always outperforms the decision list learner alone. Furthermore, using a modular architecture we investigate several algorithms for pattern ranking, the most important component of the decision list learner.

Original languageEnglish (US)
Pages48-55
Number of pages8
StatePublished - 2006
Event2006 Workshop on Adaptive Text Extraction and Mining, ATEM 2006 - Trento, Italy
Duration: Apr 4 2006 → …

Conference

Conference2006 Workshop on Adaptive Text Extraction and Mining, ATEM 2006
Country/TerritoryItaly
CityTrento
Period4/4/06 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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