Action rules mining

International Journal of Intelligent Systems

Volumn 20, Issue 7, 2005, Pages 719-736

  Tzacheva, Angelina A ^a   Ras, Zbigniew W ^a,b  

^a University of North Carolina at Charlotte   (United States)

^b INSTITUTE OF COMPUTER SCIENCE   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; DECISION THEORY; ELECTRONIC COMMERCE; GRAPH THEORY; HEURISTIC METHODS; INFORMATION RETRIEVAL; PROBLEM SOLVING; RANDOM PROCESSES; RECURSIVE FUNCTIONS; SEMANTICS; SET THEORY; SYSTEM STABILITY;

ACTION RULES; BUILD AND SEARCH TECHNIQUE; DECISION CLASSES; DISTRIBUTED INFORMATION SYSTEM (DIF);

DATA MINING;

EID: 21844458429     PISSN: 08848173     EISSN: None     Source Type: Journal    
DOI: 10.1002/int.20092     Document Type: Article

References (9)

1. Raś Z, Wieczorkowska A. Action rules: How to increase profit of a company. In: Zighed DA, Komorowski J, Zytkow J, editors. Proc Principles of Data Mining and Knowledge Discovery, PKDD' 00, Lyon, France. LNCS/LNAI, No. 1910. Berlin: Springer-Verlag; 2000. pp 587-592.
2. Raś ZW, Tsay L-S. Discovering extended action-rules (System DEAR). In: Proc Symp Intelligent Information Systems 2003, IIS'2003, Zakopane, Poland. Berlin: Springer-Verlag; 2003. pp 293-300.
3. Raś Z, Gupta S. Global action rules in distributed knowledge systems. Fundamenta Informaticae J 2002;51:175-184.
4. Raś ZW, Tzacheva A. Discovering semantic inconsistencies to improve action rules mining. In: Proc Symp Intelligent Information Systems 2003, IIS'2003, Zakopane, Poland. Berlin: Springer-Verlag; 2003. pp 301-310.
5. Pawlak Z. Rough sets and decision tables. Lecture Notes in Computer Science 208. Berlin: Springer-Verlag; 1985. pp 186-196.
6. Sowa JF. Ontology, metadata and semiotics. In: Ganter B, Mineau GW, editors. Conceptual structures: Logical, linguistic, and computational issues. LNAI 1867. Berlin: Springer-Verlag; 2000. pp 55-81.
7. Raś Z, Dardzińska A. Handling semantic inconsistencies in query answering based on distributed knowledge mining. In: Proc Symp Foundations of Intelligent Systems, ISMIS'02. LNCS/LNAI No. 2366. Berlin: Springer-Verlag; 2002. pp 66-74.
8. Fensel D. Ontologies: A silver bullet for knowledge management and electronic commerce. Berlin: Springer-Verlag; 1998.
9. Suzuki E, Kodratoff Y. Discovery of surprising exception rules based on intensity of implication. In: Zytkow JM, Quafafou M, editors. Proc Second Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Lecture Notes in Artificial Intelligence, vol. 1510. Berlin: Springer-Verlag; 1998. pp 10-18.