An overview of decision making in Rough Non-deterministic Information Analysis

Rough Non-deterministic Information Analysis (RNIA) is a rough set-based data analysis framework for Non-deterministic Information Systems (NISs). RNIA-related algorithms and software tools developed so far for rule generation provide good characteristics of NISs and can be successfully applied to decision making based on non-deterministic data. This article presents a general overview of Decision Making in RNIA including both theoretical and algorithmic aspects of the theory. We mainly focused on the following aspects of RNIA: (1) a question-answering functionality that enables decision makers to analyze data gathered in NISs, (2) an automatic decision rule generation with stability factor.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  Zdzislaw Pawlak,et al.  Some Issues on Rough Sets , 2004, Trans. Rough Sets.

[3]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[4]  Hiroshi Sakai,et al.  Rough Sets Based Rule Generation from Data with Categorical and Numerical Values , 2008, J. Adv. Comput. Intell. Intell. Informatics.

[5]  Dominik Slezak,et al.  Feedforward Concept Networks , 2004, MSRAS.

[6]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[7]  Dominik Slezak,et al.  The Lower System, the Upper System and Rules with Stability Factor in Non-deterministic Information Systems , 2009, RSFDGrC.

[8]  Hiroshi Sakai,et al.  Rules and Apriori Algorithm in Non-deterministic Information Systems , 2006, Trans. Rough Sets.

[9]  Dominik Slezak,et al.  Automatic Extraction of Decision Rules from Non-deterministic Data Systems: Theoretical Foundations and SQL-Based Implementation , 2009, FGIT-DTA.

[10]  Jan G. Bazan,et al.  Rough set algorithms in classification problem , 2000 .

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

[12]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[13]  Hiroshi Kimura,et al.  An Aspect of Decision Making in Rough Non-deterministic Information Analysis , 2009 .

[14]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[15]  Witold Lipski,et al.  On semantic issues connected with incomplete information databases , 1979, ACM Trans. Database Syst..

[16]  Ewa Orlowska,et al.  Introduction: What You Always Wanted to Know about Rough Sets , 1998 .

[17]  Ewa Orlowska,et al.  Representation of Nondeterministic Information , 1984, Theor. Comput. Sci..