HISTORY-DRIVEN TEMPLATE GENERATION IN INDUCTIVE LOGIC PROGRAMMING

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10129774" target="_blank" >RIV/00216208:11320/12:10129774 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
HISTORY-DRIVEN TEMPLATE GENERATION IN INDUCTIVE LOGIC PROGRAMMING
Original language description
Inductive logic programming is a machine learning method that combines inductive learning with the representation of hypotheses as logic programs. There exist methods that given a template find unification of variables in the template to obtain a hypothesis that subsumes all positive examples and does not subsume any negative example. In this paper we deal with the problem how to obtain the template. In particular, we suggest a method how to efficiently generate the template by remembering the history of generated templates and exploiting this history when adding predicates to a new candidate template. This method significantly outperforms the existing method based on brute-force incremental extension of the template. We demonstrate the efficiency experimentally using randomly generated structured problems.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

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

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)