1. Z. Pawlak, editor. Theorize with data using rough sets, 26 th Annual International Computer Software and Applications Conference, 2002. IEEE Computer Society, IEEE - The Institute of Electrical and Electronics Engineers. [bibtex-entry]



2. Z. Pawlak. Rough Sets. Theoretical Aspects of Reasoning about Data. Springer, Formerly Kluwer Academic Publishers, Boston, Dordrecht, London, 1991. [bibtex-entry]

1. J. Blaszczynski, S. Greco, and R. Słowiński. Multi-criteria classification: A new scheme for application of dominance-based decision rules. European Journal of Operational Research, 2006. Note: In Press. Keyword(s): multi-criteria classification, rough sets, dominance, decision rules, classifiers. [bibtex-entry]



2. S. Greco, B. Matarazzo, and R. Słowiński. Decision Rule Approach. In J. Figueira, S. Greco, and M. Ehrgott, editors, Multiple Criteria Decision Analysis: State of the Art Surveys, volume 78 of International Series in Operations Research & Management Science, chapter 13, pages 507-562. Springer, New York, 2005. Keyword(s): dominance, rough sets, decision rules, multiple criteria classification, choice and ranking. [bibtex-entry]



3. Z. Pawlak. Some remarks on conflict analysis. European Journal of Operational Research, 166(3):649-654, 2005. Keyword(s): conflict analysis, rough sets, decision analysis. [bibtex-entry]



4. V. Ananthanarayana, M. Murty, and D. Subramanian. Tree structure for efficient data mining using rough sets. Pattern Recognition Letters, 24(6):851-862, 2003. Note: Short Communication. Keyword(s): PC-tree, single database scan, dynamic mining, segment PC-tree, rough PC-tree, classification, rough sets. [bibtex-entry]



5. M. Doumpos and C. Zopounidis. Rough sets and multivariate statistical classification: A simulation study. Computational Economics, 19(3):287-301, 2002. Keyword(s): classification, rough sets theory, multivariate statistics, Monte Carlo simulation. [bibtex-entry]



6. S. Greco, B. Matarazzo, and R. Słowiński. Rough sets methodology for sorting problems in presence of multiple attributes and criteria. European Journal of Operational Research, 138(2):247-259, 2002. Keyword(s): rough sets, sorting, classification, multiple criteria decision analysis, decision rules. [bibtex-entry]



7. T.-P. Hong, L.-H. Tseng, and S.-L. Wang. Learning rules from incomplete training examples by rough sets. Expert Systems with Applications: An International Journal, 22:285-293, 2002. Keyword(s): knowledge acquisition, rough sets, machine learning, certain rule, possible rule, incomplete data set. [bibtex-entry]



8. N. Matsatsinis. CCAS: An intelligent decision support system for credit card assessment. Journal of Multi-Criteria Decision Analysis, 11(4-5):213-235, 2002. Keyword(s): machine learning, rough sets, multi-criteria decision analysis, decision support system, credit cards assessment. [bibtex-entry]



9. Z. Pawlak. Rough sets and intelligent data analysis. Information Sciences: An International Journal, 147(1-4):1-12, 2002. [bibtex-entry]



10. Z. Pawlak. Rough sets, decision algorithms and Bayes' theorem. European Journal of Operational Research, 136:181-189, 2002. Keyword(s): rough sets, decision analysis, decision support systems, Bayes' theorem. [bibtex-entry]



11. F. Questier, I. Arnaut-Rollier, B. Walczak, and D. Massart. Application of rough set theory to feature selection for unsupervised clustering. Chemometrics and Intelligent Laboratory Systems, 63:155-167, 2002. Keyword(s): rough sets, unsupervised clustering, feature selection, Wallace measure. [bibtex-entry]



12. A. Radzikowsk and E. Kerre. A comparative study of fuzzy rough sets. Fuzzy Sets and Systems, 126:137-155, 2002. Keyword(s): fuzzy set theory, rough set theory, fuzzy implicator, fuzzy rough set. [bibtex-entry]



13. M. Sarkar. Rough-fuzzy functions in classification. Fuzzy Sets and Systems, 132:353-369, 2002. Keyword(s): fuzzy sets, rough sets, rough-fuzzy sets, membership functions, classification, entropy. [bibtex-entry]



14. Q. Shen and A. Chouchoulas. A rough-fuzzy approach for generating classification rules. Pattern Recognition, 35:2425-2438, 2002. Keyword(s): pattern classification, rough sets, fuzzy sets, feature selection, rule induction. [bibtex-entry]



15. F. Tay and L. Shen. Economic and financial prediction using rough sets model. European Journal of Operational Research, 141(3):641-659, 2002. Keyword(s): rough sets model, economic and financial prediction. [bibtex-entry]



16. Z. Xu, J. Liang, C. Dang, and K. Chin. Inclusion degree: A perspective on measures for rough set data analysis. Information Sciences: An International Journal, 141:227-236, 2002. Keyword(s): rough sets, inclusion degree, data analysis, measure. [bibtex-entry]



17. S. Greco, B. Matarazzo, and R. Słowiński. Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129(1):1-47, 2001. Keyword(s): multicriteria decision analysis, rough sets, classification, sorting, choice, ranking, decision rules, conjoint measurement. [bibtex-entry]



18. S. Mitra, P. Mitra, and S. Pal. Evolutionary modular design of rough knowledge-based network using fuzzy attributes. Neurocomputing, 36:45-66, 2001. Keyword(s): soft computing, fuzzy MLP, rough sets, knowledge-based network, genetic algorithm, modular neural network. [bibtex-entry]



19. Q. Shen and A. Chouchoulas. FuREAP: A fuzzy - rough estimator of Algae populations. Artificial Intelligence in Engineering, 15:13-24, 2001. Keyword(s): Algae population estimation, fuzzy logic, rough sets, rule induction, dimensionality reduction. [bibtex-entry]



20. P. Srinivasan, M. Ruiz, D. Kraft, and J.-G. Chen. Vocabulary mining for information retrieval: Rough sets and fuzzy sets. Information Processing and Management, 37:15-38, 2001. Keyword(s): vocabulary mining, generalized rough sets, fuzzy sets, multiple vocabulary views, UMLS. [bibtex-entry]



21. N. Zhong, J. Dong, and S. Ohsuga. Rule discovery by soft induction techniques. Neurocomputing, 36:171-204, 2001. Keyword(s): inductive learning, knowledge discovery, generalization distribution table (GDT), rough sets, soft computing, uncertainty and incompleteness, background knowledge, hybrid system. [bibtex-entry]



22. K. Chakrabarty, R. Biswas, and S. Nanda. Fuzziness in rough sets. Fuzzy Sets and Systems, 110:247-251, 2000. Keyword(s): fuzzy sets, a-cut, nearest ordinary set of a fuzzy set, index of fuzziness, entropy in a fuzzy set, rough sets, roughness of a fuzzy set, fuzziness in a rough set. [bibtex-entry]



23. T.-P. Hong, T.-T. Wang, S.-L. Wang, and B.-C. Chien. Learning a coverage set of maximally general fuzzy rules by rough sets. Expert Systems with Applications: An International Journal, 19:97-103, 2000. Keyword(s): machine learning, fuzzy sets, rough sets, data mining, expert system. [bibtex-entry]



24. S. Morasca and G. Ruhe. A hybrid approach to analyze empirical software engineering data and its application to predict module fault-proneness in maintenance. The Journal of Systems and Software, 53:225-237, 2000. Keyword(s): knowledge discovery, hybrid approach, rough sets, logistic regression, empirical case studies, experience factory, fault-proneness, software maintenance. [bibtex-entry]



25. J. Peters, Z. Pawlak, and A. Skowron. A rough set approach to measuring information granules. IEEE - The Institute of Electrical and Electronics Engineers, 2000. Keyword(s): closeness, inclusion, indistinguishability, information granule, measure, rough sets, sensor. [bibtex-entry]



26. H. Wang, I. Düntsch, and G. Gediga. Classificatory filtering in decision systems. International Journal of Approximate Reasoning, 23:111-136, 2000. Keyword(s): artificial intelligence, machine learning, rough sets, data filtering, data reduction, decision system, lattice. [bibtex-entry]



27. A. Dimitras, R. Słowiński, R. Susmaga, and C. Zopounidis. Business failure prediction using rough sets. European Journal of Operational Research, 114(2):263-280, 1999. Keyword(s): business failure prediction, rough set theory, discriminant analysis, decision rules, classification. [bibtex-entry]



28. I. Jagielska, C. Matthews, and T. Whitfort. An investigation into the application of neural networks, fuzzy logic, genetic algorithms, and rough sets to automated knowledge acquisition for classification problems. Neurocomputing, 24:37-54, 1999. Keyword(s): automated knowledge acquisition, fuzzy rule extraction, fuzzy classification systems, neural networks, genetic algorithm, rough sets. [bibtex-entry]



29. J. Komorowski and A. Ohrn. Modelling prognostic of cardiac tests using rough sets. Artificial Intelligence in Medicine, 15:167-191, 1999. Keyword(s): prognostic methods, model induction, approximate reasoning, rough sets. [bibtex-entry]



30. C. Zopounidis, R. Słowiński, M. Doumpos, A. Dimitras, and R. Susmaga. Business failure prediction using rough sets: A comparison with multivariate analysis techniques. Fuzzy Economic Review, 4(1):3-33, 1999. [bibtex-entry]



31. Z. Bonikowski, E. Bryniarski, and U. Wybraniec-Skardowska. Extensions and intentions in the rough set theory. Information Sciences: An International Journal, 107:149-167, 1998. Keyword(s): approximation spaces, representative approximation spaces, rough sets, rough set inclusion, operations on rough sets. [bibtex-entry]



32. C.-C. Chan. A rough set approach to attribute generalization in data mining. Information Sciences: An International Journal, 107:169-176, 1998. Keyword(s): rough sets, data mining, inductive learning. [bibtex-entry]



33. A. Jackson, Z. Pawlak, and S. LeClair. Rough sets applied to the discovery of materials knowledge. Journal of Alloys and Compounds, 279:14-21, 1998. Keyword(s): material design, rough sets, pyramidal networks. [bibtex-entry]



34. T. Murai, H. Kanemitsu, and M. Shimbo. Fuzzy sets and binary-proximity-based rough sets. Information Sciences: An International Journal, 104:49-80, 1998. [bibtex-entry]



35. Z. Pawlak. An inquiry into anatomy of conflicts. Information Sciences: An International Journal, 109:65-78, 1998. Keyword(s): conflict analysis, conflict resolution, decision analysis, rough sets. [bibtex-entry]



36. S. Tsumoto. Extraction of experts' decision rules from clinical databases using rough set model. Intelligent Data Analysis, 2:215-227, 1998. Keyword(s): rough sets, data mining, knowledge discovery in databases, medical knowledge acquisition. [bibtex-entry]



37. Y. Yao. A Comparative study of fuzzy sets and rough sets. Information Sciences: An International Journal, 109:227-242, 1998. Keyword(s): approximation operators, fuzzy sets, model logic, many-valued logic, rough sets. [bibtex-entry]



38. Z. Pawlak. Rough set approach to knowledge-based decision support. European Journal of Operational Research, 99:48-57, 1997. Keyword(s): rough sets, fuzzy sets, decision support. [bibtex-entry]



39. A. Wakulicz-Deja and P. Paszek. Diagnose progressive encephalopathy apllying the rough set theory. International Journal of Medical Informatics, 46:119-127, 1997. Keyword(s): expert systems, machine learning, progressive encephalopathy, rough sets. [bibtex-entry]



40. Z. Pawlak. Rough sets and data analysis. IEEE - The Institute of Electrical and Electronics Engineers, pp 1-6, 1996. [bibtex-entry]



41. Z. Pawlak. Why rough sets?. IEEE - The Institute of Electrical and Electronics Engineers, pp 738-743, 1996. [bibtex-entry]



42. Z. Pawlak and R. Słowiński. Decision analysis using rough sets. International Transactions in Operational Research, 1(1):107-114, 1994. Keyword(s): decision analysis, rough set theory, vagueness, multiple criteria, sorting. [bibtex-entry]



43. Z. Pawlak. Rough sets. International Journal of Information and Computer Sciences, 11(5):341-356, 1982. [bibtex-entry]

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