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AAAI, Date: 2015/01/25 - 2015/01/30, Location: Austin, Texas, US

Publication date: 2015-01-01
Pages: 4107 -
ISSN: 978-1-57735-698-1
Publisher: AAAI Press

Proceedings 29th AAAI Conference on Artificial Intelligence

Author:

De Raedt, Luc
Bonet, Blai ; Koenig, Sven

Keywords:

Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Theory & Methods, Engineering, Electrical & Electronic, Computer Science, Engineering, PROGRAMS

Abstract:

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 learn- ing 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.