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Inductive logic programming

Known as: ILP 
Inductive logic programming (ILP) is a subfield of machine learning which uses logic programming as a uniform representation for examples, background… Expand
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Papers overview

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2014
2014
Inductive Logic Programming (ILP) is a classic machine learning technique that learns first-order rules from relational… Expand
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2011
2011
In this paper we discuss the design of an Inductive Logic Programming (ILP) system in Answer Set Programming (ASP) and more in… Expand
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Highly Cited
2009
Highly Cited
2009
In the last few years, there has been a growing interest in the adoption of declarative paradigms for modeling and verifying… Expand
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Highly Cited
2008
Highly Cited
2008
Probabilistic inductive logic programming aka. statistical relational learning addresses one of the central questions of… Expand
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Highly Cited
2006
Highly Cited
2006
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A… Expand
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Highly Cited
2004
Highly Cited
2004
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central… Expand
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Highly Cited
2004
Highly Cited
2004
Relief algorithms are general and successful attribute estimators. They are able to detect conditional dependencies between… Expand
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Highly Cited
2001
Highly Cited
2001
In this paper, we explored a learning approach which combines different learning methods in inductive logic programming (ILP) to… Expand
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Highly Cited
1997
Highly Cited
1997
Propositional logic.- First-order logic.- Normal forms and Herbrand models.- Resolution.- Subsumption theorem and refutation… Expand
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Highly Cited
1996
Highly Cited
1996
This paper presents recent work using the CHILL parser acquisition system to automate the construction of a natural-language… Expand
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