Statistical techniques for free-text processing

  • Authors:
  • John M. Morris

  • Affiliations:
  • PAR Corp., Rome, NY

  • Venue:
  • ACM SIGLASH Newsletter
  • Year:
  • 1980

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Abstract

Over the past eight years we have developed statistical methods for characterizing, classifying, and retrieving brief natural-language messages. Our goal was to provide a tool for people who had to deal with enormous numbers of heterogeneous documents, using ill-defined criteria of relevance and interest. Initially, we worked with a large, general-purpose system, the On-Line Pattern Analysis and Recogition System (OLPARS). More recently, we have developed a system called Message Extraction Through Estimation of Relevance (METER). Our present aim is the construction of a Testbed system for further studies and the development of more complex systems.