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Biography and future challenges

delete2011-09-05
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OA
AI
S
Stephen Muggleton *
L
Luc De Raedt
D
David Poole
I
Ivan Bratko
P
Peter Flach
K
Katsumi Inoue
A
Ashwin Srinivasan
DOI:10.1007/s10994-011-5259-2delete
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Abstract

Abstract

En 中文
Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and challenging real-world applications. Lastly, by projection we suggest directions for research which will help the subject coming of age.
Keywords:
Inductive Logic Programming
(Statistical) relational learning
Structured data in Machine Learning

Journal

Machine Learning cover
Machine Learning
IF:
2.9
Papers:
2.6K
Citations:
3.4W

Organization

U
University of Ljubljana
Scholars:
1.5W
Papers: 1.3W
Citations: 1.7W
N
national institute of informatics (nii) - japan
Scholars:
451
Papers: 418
Citations: 0
K
KU Leuven
Scholars:
5.7W
Papers: 5.2W
Citations: 8.1W
R
research organization of information & systems (rois)
Scholars:
2.7K
Papers: 3.1K
Citations: 2
I
Imperial College London
Scholars:
8.3W
Papers: 7.3W
Citations: 11.1W
U
University of Bristol
Scholars:
3.1W
Papers: 3.0W
Citations: 5.3W
U
University of British Columbia
Scholars:
6.9W
Papers: 6.1W
Citations: 8.6W
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