Inductive logic programming

Inductive logic programming (ILP) is a machine learning approach, which uses techniques of logic programming. From a database of facts and expected results, which are divided into positive and negative examples, an ILP system tries to derive a logic program that proves all the positive and none of the negative examples.

Schema: positive examples + negative examples + background knowledge = rules.

Inductive logic programming is particularly useful in natural language processing.

Implementations

• Aleph ( http://web.comlab.ox.ac.uk/oucl/research/areas/machlearn/Aleph )
• Foil ( ftp://ftp.cs.su.oz.au/pub/foil6.sh )
• Lime ( http://cs.anu.edu.au/people/Eric.McCreath/lime.html )

References

• Adapted from the Wikipedia article, "Inductive_logic_programming" http://en.wikipedia.org/wiki/Inductive_logic_programming, used under the GNU Free Documentation License