Decomposition, Merging, and Refinement Approach to Boost Inductive Logic Programming Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10129785" target="_blank" >RIV/00216208:11320/12:10129785 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-642-33185-5_21" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-642-33185-5_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-33185-5_21" target="_blank" >10.1007/978-3-642-33185-5_21</a>
Alternative languages
Result language
angličtina
Original language name
Decomposition, Merging, and Refinement Approach to Boost Inductive Logic Programming Algorithms
Original language description
Inductive Logic Programming (ILP) deals with the problem of finding a hypothesis covering positive examples and excluding negative examples. It uses first-order logic as a uniform representation for examples and hypothesis. In this paper we propose a method to boost any ILP learning algorithm by first decomposing the set of examples to subsets and applying the learning algorithm to each subset separately, second, merging the hypotheses obtained for the subsets to get a single hypothesis for the completeset of examples, and finally refining this single hypothesis to make it shorter. The proposed technique significantly outperforms existing approaches.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP202%2F12%2FG061" target="_blank" >GBP202/12/G061: Center of excellence - Institute for theoretical computer science (CE-ITI)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Computer Science
ISSN
0302-9743
e-ISSN
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Volume of the periodical
2012
Issue of the periodical within the volume
7557
Country of publishing house
DE - GERMANY
Number of pages
11
Pages from-to
184-194
UT code for WoS article
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EID of the result in the Scopus database
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