An Alternative Approach to Mining Association Rules

An alternative approach to mining association rules is described. Some special techniques and algorithms are used that lead to a much richer syntax of association rules with only linear complexity of computation. A free and open system LISp-Miner implements these algorithms and can serve as a demonstration of used techniques. The same techniques can be used in other kinds of mining e.g. multi-relation mining and conditional frequency analysis.

[1]  Harrie de Swart Theory and Applications of Relational Structures as Knowledge Instruments , 2003 .

[2]  Jan Rauch,et al.  Reporting Data Mining Results in a Natural Language , 2005, Foundations of Data Mining and knowledge Discovery.

[3]  Jan Rauch Definability of Association Rules in Predicate Calculus , 2006, Foundations and Novel Approaches in Data Mining.

[4]  Petr Hájek,et al.  GUHA for personal computers , 1995 .

[5]  Jan Rauch,et al.  Mining for Patterns Based on Contingency Tables by KL-Miner - First Experience , 2006, Foundations and Novel Approaches in Data Mining.

[6]  Tsau Young Lin,et al.  Finding Association Rules Using Fast Bit Computation: Machine-Oriented Modeling , 2000, ISMIS.

[7]  Jan Rauch,et al.  Classes of Four-Fold Table Quantifiers , 1998, PKDD.

[8]  Jan Rauch,et al.  SDS-rules and association rules , 2004, SAC '04.

[9]  Jan Rauch Some remarks on computer realizations of GUHA procedures , 1978 .

[10]  Tsau Young Lin,et al.  Foundations and Novel Approaches in Data Mining , 2006, Studies in Computational Intelligence.

[11]  Petr Berka,et al.  Automated Knowledge Acquisition for PROSPECTOR-like Expert Systems , 1994, ECML.

[12]  Heikki Mannila,et al.  Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.

[13]  T. Havránek,et al.  Mechanizing Hypothesis Formation: Mathematical Foundations for a General Theory , 1978 .

[14]  Jan Rauch Logical Calculi for Knowledge Discovery in Databases , 1997, PKDD.

[15]  Milan Šimůnek Academic KDD Project LiSp-Miner , 2003 .

[16]  Jan Rauch,et al.  Interesting Association Rules and Multi-relational Association Rules , 2002 .

[17]  Jan Rauch,et al.  Logic of Association Rules , 2004, Applied Intelligence.