Rough Sets

Communications of the ACM

Volumn 38, Issue 11, 1995, Pages 88-95

  Pawlak, Lazislaw ^a   Grzvmala Busse, Lerzv ^b   Slowinski, Roman ^c   Ziarko, Wojciech ^d  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b UNIVERSITY OF KANSAS   (United States)

^c POZNAN UNIVERSITY OF TECHNOLOGY   (Poland)

^d UNIVERSITY OF REGINA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; ARTIFICIAL INTELLIGENCE; COMPUTER SOFTWARE; DATA PROCESSING; DATABASE SYSTEMS; DECISION SUPPORT SYSTEMS; DECISION THEORY; FUNCTIONS; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING;

DECISION ANALYSIS; KNOWLEDGE DISCOVERY; ROUGH SET THEORY;

SET THEORY;

EID: 0029405527     PISSN: 00010782     EISSN: 15577317     Source Type: Journal    
DOI: 10.1145/219717.219791     Document Type: Article

References (25)

1. Dubois, D., and Prade, H. Foreword. Rough Sets: Theoretical Aspects of Reasoning about Data, by Z. Pawlak. Kluwer, Dordrecht, Netherlands, 1991.
2. Grzymala-Busse, J. W. Knowledge acquisition under uncertainty A rough set approach./. Intel Rob. Syst. 1, 1 (1988), 3–16.
3. Grzymala-Busse, J. W. Managing Uncertainty in Expert Systems. Kluwer, Dordrecht, Netherlands, 1991.
4. Grzymala-Busse, J. W. LERS—A system for learning from examples based on rough sets. In Intelligent Decision Support. Handbook of Applications and Advances of the Rough Sets Theory. R. Slowinski, Ed. Kluwer, Dordrecht, Boston, London, pp. 1992, 3–18.
5. Grzymala-Busse, D. M., and Grzymala-Busse, J. W. Evaluation of machine learning approach to knowledge acquisition. In Proceedings of the 14th International Avignon Conference. (Paris, May 30-June 3). 1994, pp. 183–192.
6. Gunn, J. D., and Grzymala-Busse, J. W. Global temperature stability by ruIe induction: An interdisciplinary bridge. Hum. Ecol. 22 (1994), 59–81.
7. Krusinska, E., Slowinski, R., and Stefanowski, J. Discriminant versus rough set approach to vague data analysis. Appl. Stochastic Models and Data Anal. 8 (1992), 43–56.
8. Krysinski, J. Rough set approach to the analysis of the structure-activity relationship of quaternary imidazolium compounds. Arzneimittel-Eorschung, (Drug Research) 40, 7 (1990), 795–799.
9. Lin, T. Y., Ed. Proceedings of the RSSC'95, Third International Workshop on Rough Sets and Soft Computing (San Jose, Calif. )1994.
10. Nowicki, R., Slowinski, R., and Stefanowski, J. Evaluation of vibroacoustic diagnostic symptoms by means of the rough set theory. Comput. Ind. 20 (1992), 141–152.
11. Pawlak, Z. Rough sets. Int.J. Comput. Inf. Sci. 11 (1982), 341–356.
12. Pawlak, Z. Rough sets. In Theoretical Aspects of Reasoning About Data. Kluwer, Netherlands, 1991.
13. of 13. Pawlak, Z., and Skowron, A. Rough membership functions. In R. R. Yaeger, M. Fedrizzi, and J. Kacprzyk, Eds. Advances in theDemp-ster-Shafer Evidence. Wiley, New York, 1994, 251–271. Theory.
14. Pawlak, Z., and Slowinski, R. Rough set approach to multi-attribute decision analysis. Invited Review, Eur.J. ofOper. Res. 72 (1994), 443–459.
15. Skowron, A., and Grzymala-Busse, J. W. From rough set theory to evidence theory. In Advances in the Dempster-Shafer Theory of Evidence. R. R. Yaeger, M. Fedrizzi, and J. Kacprzyk, Eds. Wiley, New York, 1994, 193–236.
16. Skowron, A., and Rauszer, C. The discernibility matrices and functions in information systems. Intelligent Decision Support. Handbook of Advances and Applications of the Rough Set Theory. R. Slowinski, Ed. Kluwer, Dordrecht, Netherlands, 1992, 331–362.
17. Slowinski, K. Rough classification of HSV patients. In Intelligent Decision Support. Handbook of Advances and Applications of the Rough Set Theory, R. Slowinski, Ed. Kluwer, Dordrecht, Netherlands, 1992, 77–94.
18. Slowinski, R., Ed. Intelligent Decision Support. Handbook of Applications and Advances of the Rough Sets Theory. Kluwer, Dordrecht, Netherlands, 1992.
19. Slowinski, R., and Zopounidis, C. Rough set sorting of firms according to bankruptcy risk. In Applying Multiple Criteria Aid for Decision to Environmental Management. M. Paruccini, Ed. Kluwer, Dordrecht, Netherlands, 1994, 339–357.
20. Szladow, A. Datalogic/R: Mining the knowledge in databases. PC AI 7, 1 (1993), 40–41.
21. Szladow, A., and Ziarko, W. Rough sets: Working with imperfect data. Al Expert 7 (1993), 36–41.
22. Ziarko, W. The discovery, analysis and representation of data dependencies in databases. Knowledge Discovery in Databases, G. Piatetsky-Shapiro, and W. J. Frawley, Eds. AAAI Press/MIT Press, 1991, 177–195.
23. Ziarko, W. Variable precision rough sets model. J. Comput. Syst. Scie. 46 (1993), 39–59.
24. Ziarko, W., Ed. Rough sets, fuzzy sets and knowledge discovery. In Proceedings of RSKD'94 Workshop (Banff). Springer-Verlag, Berlin, 1994.
25. Ziarko, W., Golan, R., and Edwards, D. An application of datalog-ic/R knowledge discovery tool to identify strong predictive rules in stock market data. In Proceedings of AAAI Workshop on Knowledge Discovery in Databases, (Washington, D.C.). 1993, 89–101.