%0 Journal Article %1 Pawlak2007a %A Pawlak, Zdzislaw %A Skowron, Andrzej %D 2006 %J Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland %K (in)Discernibility; Approximation Boolean Decision Dependencies Information Reducts; Rough Set Vague and approximations; attributes; concepts; decision functions; membership of reasoning rules; sets; spaces; systems; %P 3-27 %T Rudiments of rough sets %V Information Sciences 177 (2007) %X Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets in their programs. Rough set theory has led to many interesting applications and extensions. It seems that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences, especially in research areas such as machine learning, intelligent systems, inductive reasoning, pattern recognition, mereology, knowledge discovery, decision analysis, and expert systems. In the article, we present the basic concepts of rough set theory and point out some rough setbased research directions and applications.

@article{Pawlak2007a, abstract = {Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets in their programs. Rough set theory has led to many interesting applications and extensions. It seems that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences, especially in research areas such as machine learning, intelligent systems, inductive reasoning, pattern recognition, mereology, knowledge discovery, decision analysis, and expert systems. In the article, we present the basic concepts of rough set theory and point out some rough setbased research directions and applications.}, added-at = {2013-08-04T14:29:00.000+0200}, author = {Pawlak, Zdzislaw and Skowron, Andrzej}, biburl = {https://www.bibsonomy.org/bibtex/22cb92eadd8fdaa81ffd64899170ea412/francesco.k}, interhash = {5cdf23c71efc7b34fcb6ce36cd0d01ba}, intrahash = {2cb92eadd8fdaa81ffd64899170ea412}, journal = {Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland}, keywords = {(in)Discernibility; Approximation Boolean Decision Dependencies Information Reducts; Rough Set Vague and approximations; attributes; concepts; decision functions; membership of reasoning rules; sets; spaces; systems;}, owner = {23}, pages = {3-27}, timestamp = {2013-08-04T14:29:01.000+0200}, title = {Rudiments of rough sets}, volume = {Information Sciences 177 (2007)}, year = 2006 }