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Languages for Learning and Mining
KU Leuven, Department of Computer Science, Heverlee, Belgium.ORCID-id: 0000-0002-6860-6303
2015 (engelsk)Inngår i: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence / [ed] B. Bonet; S. Koenig, AAAI Press, 2015, Vol. 6, s. 4107-4111Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Applying machine learning and data mining to novel applications is cumbersome. This observation is the prime motivation for the interest in languages for learning and mining. This note provides a gentle introduction to three types of languages that support machine learning and data mining: inductive query languages, which extend database query languages with primitives for mining and learning, modelling languages, which allow to declaratively specify and solve mining and learning problems, and programming languages, that support the learning of functions and subroutines. It uses an example of each type of language to introduce the underlying ideas and puts them into a common perspective. This then forms the basis for a short analysis of the state-of-the-art

sted, utgiver, år, opplag, sider
AAAI Press, 2015. Vol. 6, s. 4107-4111
Serie
Proceedings of the AAAI Conference on Artificial Intelligence, ISSN 2159-5399, E-ISSN 2374-3468
Emneord [en]
artificial intelligence, machine learning, data mining, languages
HSV kategori
Identifikatorer
URN: urn:nbn:se:oru:diva-91916ISI: 000485625504028Scopus ID: 2-s2.0-84961230995ISBN: 9781577357049 (tryckt)OAI: oai:DiVA.org:oru-91916DiVA, id: diva2:1556725
Konferanse
29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference (IAAI 2015), Austin, United States, January 25-30, 2015
Merknad

Funding Agencies:

EU ICON FP7 Project  

BOF GOA project on Declarative Modeling for Learning and Mining  

Tilgjengelig fra: 2021-05-24 Laget: 2021-05-24 Sist oppdatert: 2023-05-29bibliografisk kontrollert

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De Raedt, Luc

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Totalt: 47 treff
RefereraExporteraLink to record
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Referensformat
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
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  • nn-NB
  • sv-SE
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