Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00185744" target="_blank" >RIV/68407700:21230/11:00185744 - isvavai.cz</a>
Result on the web
<a href="http://www.springerlink.com/content/w450n21140245x78/" target="_blank" >http://www.springerlink.com/content/w450n21140245x78/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10462-010-9181-y" target="_blank" >10.1007/s10462-010-9181-y</a>

Result language
angličtina
Original language name
Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming
Original language description
We describe a new approach to the application of stochastic search in Inductive Logic Programming (ILP). Contrary to traditional approaches we do not focus directly on evolving logical concepts. Instead, our refinement-based approach uses the stochasticoptimization process to iteratively adapt the initial working concept. It enables using available background knowledge both for efficiently restricting the search space and for directing the search. Thereby, the search is more flexible, less problem-specific and the framework can be easily used with any stochastic search algorithm within ILP domain. Experimental results on several data sets verify the usefulness of this approach.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Project
<a href="/en/project/GAP103%2F10%2F1875" target="_blank" >GAP103/10/1875: Learning from Theories</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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