Summer Semester 2010/11
Summer Semester 2011/12
Multi-Relational Data Mining ITI2101
Course content:
1. Introduction to multi-relational data mining (MRDM).
2. Overview of tasks and methods of data mining.
3. Main tasks of MRDM: classification.
4. Main tasks of MRDM: description.
5. Main tasks of MRDM: clustering.
6. Upgrading propositional algorithms to a relational form.
7. Structural and propositional approaches. Propositionalization.
8. Summary.
Learning outcomes: Knowledge of basic tasks and methods of multi-relational data mining. The ability to select
the appropriate tool for solving a problem from the field of multi-relational data mining.
(in Polish) Rodzaj przedmiotu
Course coordinators
Bibliography
a) basic references:
1. Dzeroski S., Lavrac N. (eds.): Relational Data Mining. Springer, Berlin, 2001.
2. Knobbe A.: Multi-Relational Data Mining, IOS Press, 2006.
3. Dzeroski S.: Multi-relational data mining: An introduction. SIGKDD Explorations Newsletter 5(1), pp. 1 - 16, 2003.
b) supplementary references:
1. Hand D., Mannila H., Smyth P.: Data mining (in Polish), Wydawnictwa Naukowo-Techniczne, 2005.
2. Lavrac N., Dzeroski S.: Inductive Logic Programming: Techniques and Applications. Ellis Horwood, New York, 1994.
3.Cichosz P.: Machine learning (in Polish). WNT, Warsaw, 2000.