TY  - BOOK
AU  - Ślęzak,Dominik
AU  - Yao,JingTao
AU  - Peters,James F.
AU  - Ziarko,Wojciech
AU  - Hu,Xiaohua
ED  - SpringerLink (Online service)
TI  - Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 10th International Conference, RSFDGrC 2005, Regina, Canada, August 31 - September 3, 2005, Proceedings, Part II 
T2  - Lecture Notes in Computer Science,
SN  - 9783540318248
AV  - Q334-342 
U1  - 006.3 23
PY  - 2005///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Database management
KW  - Information storage and retrieval systems
KW  - Artificial intelligence
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Artificial Intelligence (incl. Robotics)
KW  - Information Storage and Retrieval
KW  - Database Management
KW  - Mathematical Logic and Formal Languages
KW  - Computation by Abstract Devices
KW  - Pattern Recognition
N1  - Invited Papers -- Rough Set Software -- Data Mining -- Hybrid and Hierarchical Methods -- Information Retrieval -- Image Recognition and Processing -- Multimedia Applications -- Medical Applications -- Bioinformatic Applications -- Web Content Analysis -- Business Applications -- Security Applications -- Industrial Applications -- Embedded Systems and Networking -- Intelligent and Sapient Systems
N2  - This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005. This conference followed in the footsteps of inter- tional events devoted to the subject of rough sets, held so far in Canada, China, Japan,Poland,Sweden, and the USA. RSFDGrC achievedthe status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signi?cant results in many areas such as ?nance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications. In the case of this event, additional e?ort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas
UR  - http://dx.doi.org/10.1007/11548706
ER  -