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Informing Datalog through Language Intelligence – A Personal Perspective

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Book cover Datalog Reloaded (Datalog 2.0 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6702))

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Abstract

Despite AI’s paramount aim of developing convincing similes of true natural language “understanding”, crucial knowledge that is increasingly becoming available to computers in text form on web repositories remains in fact decipherable only by humans. In this position paper, we present our views on the reasons for this failure, and we argue that for bringing computers closer to becoming true extensions of the human brain, we need to endow them with a cognitively-informed web by integrating new methodologies in the inter-disciplines involved, around the pivot of Logic Programming and Datalog.

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Author information

Authors and Affiliations

  1. GRLMC-Research Group on Mathematical Linguistics, Rovira i Virgili University, 43002, Tarragona, Spain

    Veronica Dahl

  2. Department of Computer Science and Logic and Functional Programming Group, Simon Fraser University, Burnaby, B.C., Canada

    Veronica Dahl

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  1. Veronica Dahl
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Editors and Affiliations

  1. Department of Computer Science, Oxford University, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK

    Oege de Moor

  2. Department of Computer Science, University of Oxford, UK

    Georg Gottlob , Tim Furche  & Andrew Sellers ,  & 

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Dahl, V. (2011). Informing Datalog through Language Intelligence – A Personal Perspective. In: de Moor, O., Gottlob, G., Furche, T., Sellers, A. (eds) Datalog Reloaded. Datalog 2.0 2010. Lecture Notes in Computer Science, vol 6702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24206-9_10

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  • DOI: https://doi.org/10.1007/978-3-642-24206-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24205-2

  • Online ISBN: 978-3-642-24206-9

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