Experiments with interactive question-answering

  • Authors:
  • Sanda Harabagiu;Andrew Hickl;John Lehmann;Dan Moldovan

  • Affiliations:
  • Language Computer Corporation, Richardson, Texas;Language Computer Corporation, Richardson, Texas;Language Computer Corporation, Richardson, Texas;Language Computer Corporation, Richardson, Texas

  • Venue:
  • ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
  • Year:
  • 2005

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Abstract

This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Generated off-line from topic representations of complex scenarios, predictive questions represent requests for information that capture the most salient (and diverse) aspects of a topic. We present experimental results from large user studies (featuring a fully-implemented interactive Q/A system named FERRET) that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a Q/A dialogue.