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Logic and the Automatic Acquisition of Scientific Knowledge

King, Ross Donald (author)
Department of Computer Science, University of Wales, Aberystwyth Ceridigion, Wales, U.K.
Karwath, Andreas (author)
Department of Computer Science, University of Wales, Aberystwyth Ceridigion, Wales, U.K.
Clare, Amanda (author)
Department of Computer Science, University of Wales, Aberystwyth Ceridigion, Wales, U.K.
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DeHaspe, Luc (author)
PharmaDM, Brussels, Belgium
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Department of Computer Science, University of Wales, Aberystwyth Ceridigion, Wales, UK. PharmaDM, Brussels, Belgium (creator_code:org_t)
Linköping University Electronic Press, 2000
English 10 s.
Series: Linköping Electronic Articles in Computer and Information Science, 1401-9841 ; Vol.5:31
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  • This paper is a manifesto. It argues that:Science is experiencing an unprecedented explosion in the amount of available data.Traditional data analysis methods cannot deal with this increased quantity of data.There is therefore an urgent need to automate the process of refining scientific data into scientific knowledge.Inductive logic programming (ILP) is the data analysis framework best suited for this task.We describe an example of using ILP to analyse a large and complex bioinformatic database which produced unexpected and interesting scientific results. We then point a possible way forward to integrating machine learning with scientific databases to form intelligent inductive databases.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)

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