About: Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Inductive logic programming is a subfield of machine learning which uses first-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 find 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.
  • Inductive logic programming is a subfield of machine learning which uses first-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 find 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. (en)
Title
  • Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming
  • Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming (en)
skos:prefLabel
  • Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming
  • Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming (en)
skos:notation
  • RIV/00216208:11320/12:10129947!RIV13-MSM-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I, P(GA201/08/0509)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 128510
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/12:10129947
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Inductive Logic Programming; Learning Hypotheses; Constraint Satisfaction (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [DBE6E9CC26B2]
http://linked.open...i/riv/mistoVydani
  • Berlin / Heidelberg
http://linked.open...vEdiceCisloSvazku
  • 3
http://linked.open...i/riv/nazevZdroje
  • Encyclopedia of the Sciences of Learning
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...v/pocetStranKnihy
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Barták, Roman
  • Kuželka, Ondřej
  • Železný, Filip
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-1-4419-1428-6_1794
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-1-4419-1427-9
http://localhost/t...ganizacniJednotka
  • 11320
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 48 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software