Robust methods in analysis of natural language data

  • Authors:

  • Afzal Ballim;Vincenzo Pallotta

  • Affiliations:

  • School of Information and Communication Sciences, Swiss Federal Institute of Technology, Lausanne, Switzerland;School of Information and Communication Sciences, Swiss Federal Institute of Technology, Lausanne, Switzerland

  • Venue:
  • Natural Language Engineering
  • Year:
  • 2002

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Abstract

The automated analysis of natural language data has become a central issue in the design of intelligent information systems. Processing unconstrained natural language data is still considered as an AI-hard task. However, various analysis techniques have been proposed to address specific aspects of natural language. In particular, recent interest has been focused on providing approximate analysis techniques, assuming that when perfect analysis is not possible, partial results may be still very useful.