Title (abbrev)

Title (full)

Last update

Induction of first-order rules and constraints for knowledge dis

b D, Y

Category

WWW

ILP

http://www.cs.bris.ac.uk/Research/MachineLearning/royal.html

Description

Adaptivity and the ability to make use of knowledge implicitly present in low-level data are of primary importance for enhancing business and administrative processes in Europe. With data warehousing in relational databases becoming more and more popular, there is increasing awareness that structural or relational learning as investigated in the field of Inductive Logic Programming (ILP) is a key technique for knowledge discovery. The main goals of this project are to enhance existing techniques and develop new ILP algorithms that can be used as efficient tools for solving hard problems, using induced first-order classification rules and integrity constraints.

Coordinating Group

2. University of Bristol, MLBC group
3. Jozef Stefan Institute, Department of Intelligent
4. , GPDS
5. RHUL, COLT group
6. Paisley Uni, ACIRU
7. UNIFI, MLNN
8. IC, CBL
9. Sentient Machine Research
10. SHU, LEVIS

Comment (optional)

This research is supported by the Royal Society under a Joint Project with Central and Eastern Europe.