Inducing Probabilistic Relational Rules from Probabilistic ExamplesShow others and affiliations
2015 (English)In: Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence / [ed] Wooldridge M.; Yang Q., Palo Alto: AAAI Press, 2015, p. 1835-1842Conference paper, Published paper (Refereed)
Abstract [en]
We study the problem of inducing logic programs in a probabilistic setting, in which both the example descriptions and their classification can be probabilistic. The setting is incorporated in the probabilistic rule learner ProbFOIL(+), which combines principles of the rule learner FOIL with ProbLog, a probabilistic Prolog. We illustrate the approach by applying it to the knowledge base of NELL, the Never-Ending Language Learner.
Place, publisher, year, edition, pages
Palo Alto: AAAI Press, 2015. p. 1835-1842
Series
IJCAI International Joint Conference on Artificial Intelligence, ISSN 1045-0823
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:oru:diva-91704ISI: 000442637801128Scopus ID: 2-s2.0-84949921090ISBN: 9781577357384 (print)OAI: oai:DiVA.org:oru-91704DiVA, id: diva2:1553458
Conference
24th International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina, July 25-31, 2015
Note
Funding Agency:
FWO
2021-05-102021-05-102021-05-11Bibliographically approved