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Combining Structured and Unstructured Knowledge Sources for Question Answering in Watson

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Data Integration in the Life Sciences (DILS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7348))

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Abstract

One of the classical challenges of Artificial Intelligence research has been to build automatic, open-domain question answering (QA) systems. The goal is not merely to retrieve documents containing answers to questions, or to query databases known to contain the answers. Rather, open-domain question answering systems must accept any question on any topic, find relevant information from possibly disparate sources, synthesize an answer, explain the evidence supporting the answer and provide an indication of the systems confidence that the answer is correct.

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Author information

Authors and Affiliations

  1. IBM Research, Thomas J. Watson Research Center, Yorktown Heights, NY, 10598, USA

    Ken Barker

Authors
  1. Ken Barker
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Editor information

Editors and Affiliations

  1. US National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, 20894, Bethesda, MD, USA

    Olivier Bodenreider  & Bastien Rance  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Barker, K. (2012). Combining Structured and Unstructured Knowledge Sources for Question Answering in Watson. In: Bodenreider, O., Rance, B. (eds) Data Integration in the Life Sciences. DILS 2012. Lecture Notes in Computer Science(), vol 7348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31040-9_5

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  • DOI: https://doi.org/10.1007/978-3-642-31040-9_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31039-3

  • Online ISBN: 978-3-642-31040-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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