Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10129947" target="_blank" >RIV/00216208:11320/12:10129947 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21230/12:00202362

Result on the web

<a href="http://dx.doi.org/10.1007/978-1-4419-1428-6_1794" target="_blank" >http://dx.doi.org/10.1007/978-1-4419-1428-6_1794</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-1-4419-1428-6_1794" target="_blank" >10.1007/978-1-4419-1428-6_1794</a>

Result language

angličtina

Original language name

Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming

Original language description

Inductive logic programming is a sub?eld of machine learning which uses ?rst-order logic as a uniform representation of examples, background knowledge, and hypotheses. In many works, it is assumed that examples are clauses and the goal is to ?nd a consistent hypothesis H, that is, a clause entailing all positive examples and no negative example. We apply constraint satisfaction to learn hypotheses in ILP.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

IN - Informatics

OECD FORD branch

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Project

<a href="/en/project/GA201%2F08%2F0509" target="_blank" >GA201/08/0509: LeCoS: merging machine LEarning and COnstraint Satisfaction</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name

Encyclopedia of the Sciences of Learning

ISBN

978-1-4419-1427-9

Number of pages of the result

4

Pages from-to

777-780

Number of pages of the book

4300

Publisher name

Springer

Place of publication

Berlin / Heidelberg

UT code for WoS chapter

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