Towards a Practical Approach to Discover Internal Dependencies in Rule-Based Knowledge Bases

In this paper, we intend to introduce the conception of discovering the knowledge about rules saved in large rule-based knowledge bases, both generated automatically and acquired from human experts in the classical way. This paper presents a preliminary study of a new project in which we are going to join the two approaches: the hierarchical decomposition of large rule bases using cluster analysis and the decision units conception. Our goal is to discover useful, potentially implicit and directly unreadable information from large rule sets.

[1]  Alicja Wakulicz-Deja,et al.  Decision Units as a Tool for Rule Base Modeling and Verification , 2003, IIS.

[2]  Alicja Wakulicz-Deja,et al.  Verification of Rule Knowledge Bases Using Decision Units , 2000, Intelligent Information Systems.

[3]  Simon Parsons,et al.  Principles of Data Mining by David J. Hand, Heikki Mannila and Padhraic Smyth, MIT Press, 546 pp., £34.50, ISBN 0-262-08290-X , 2004, The Knowledge Engineering Review.

[4]  Usama M. Fayyad,et al.  Knowledge Discovery in Databases: An Overview , 1997, ILP.

[5]  C. Grundmann.  Humboldt‐Universität Berlin , 1950 .

[6]  Jan M. Zytkow,et al.  Handbook of Data Mining and Knowledge Discovery , 2002 .

[7]  Z. Pawlak,et al.  Rough sets perspective on data and knowledge , 2002 .

[8]  Andrzej Skowron,et al.  Rough Set Approach to KDD (Extended Abstract) , 2008, RSKT.

[9]  Andrzej Skowron,et al.  On Minimal Rule Sets for Almost All Binary Information Systems , 2007, Fundam. Informaticae.

[10]  Alicja Wakulicz-Deja,et al.  The Way of Rules Representation in Composited Knowledge Bases , 2009, ICMMI.

[11]  Alicja Wakulicz-Deja,et al.  Towards Modular Representation of Knowledge Base , 2006, Intelligent Information Systems.

[12]  Heikki Mannila,et al.  Principles of Data Mining , 2001, Undergraduate Topics in Computer Science.

[13]  Andrzej Skowron,et al.  Rough set approach to KDD , 2008, RSKT 2008.

[14]  Agnieszka Nowak-Brzezińska,et al.  WYBÓR ALGORYTMU GRUPOWANIA A EFEKTYWNOŚĆ WYSZUKIWANIA DOKUMENTÓW , 2010 .

[15]  Z. Pawlak,et al.  A Rough Set Perspective on Data andKnowledge ? , 1999 .