@BOOK { Rsds4419,
title = {Rough Sets and Knowledge Technology}, 
booktitle = {Proceedings of the Second International Conference on Rough Sets and Knowledge Technology (RSKT'2007)}, 
conference = {Rough Sets and Knowledge Technology}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 4481, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2007, 
editor = {Yao, Jing Tao and Lingras, Pawan and Wu, Wei-Zhi and Szczuka, Marcin and Cercone, N. and Slezak, Dominik}, 
url = {http://www.springer.com/computer/artificial/book/978-3-540-72457-5}, 
isbn = {978-3-540-72457-5}, 
abstract = {This book constitutes the refereed proceedings of the Second International Conference on Rough Sets and Knowledge Technology, RSKT 2007, held in Toronto, Canada in May 2007 in conjunction with the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2007, both as part of the Joint Rough Set Symposium, JRS 2007. The 67 revised full papers presented together with three invited papers were carefully reviewed and selected from a total of 319 general submissions to the JRS 2007 symposium. The papers are organized in topical sections on rough set foundations, multiple criteria decision analysis, biometrics, kansei engineering, autonomy-oriented computing, soft computing in bioinformatics, ubiquitous computing and networking, rough set algorithms, knowledge representation and reasoning, genetic algorithms, and rough set applications. Written for: Researchers and professionals}, 
keywords = {algorithmic learning, association mining, attribute reducts, biometrics, classification, clustering, data analysis, decision making, energy efficiency, evolutionary algorithm, fuzzy sets, genetic algorithms, granular computing, intelligent systems, kansei engineering, knowledge discovery, knowledge reduction, machine learning, memetic algorithm, modeling, neural networks, object recognition, pattern recognition, probabilistic methods, requirements engineering, rough sets, semantic Web, support vector machines, vague knowledge, wireless sensor networks, }, 
}