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"Rough sets : selected methods and applications in management and engineering provides context to rough set theory, with each chapter exploring a real-world application of rough sets."

"This book constitutes the refereed proceedings of the 8th International Conference on Rough Sets and Current Trends in Computing, RSCTC, held in Chengdu, China, in August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 55 revised full papers presented together with one keynote paper were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets and its applications, current trends in computing, decision-theoretic rough set model and applications, formal concept analysis and granular computing, mining complex data with granular computing, and data mining competition."

"This book constitutes the refereed proceedings of the 7th International Conference on Rough Sets and Knowledge Technology, RSKT 2012, held in Chengdu, China during August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 63 revised papers (including 42 regular and 21 short papers) were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets and its generalizations, rough sets in data and knowledge processing, knowledge technology, advances in granular computing (AGC 2012 workshop), decision-theoretic rough set model and applications (special session), intelligent decision making and granular computing (special session), rough set foundations (special session)."

"Volume XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning, the introduction of multi-valued near set theory, the advent of a complete system that supports a rough-near set approach to digital image analysis, and an exhaustive study of the mathematics of vagueness."

"This study differs from previous studies by applying multivariate statistical analysis and multi-criterion decision-making methods to the improvement of service quality. We use the rough set theory (RST) with a flow graph approach to determine customer attitudes regarding service quality, which can assist managers in developing strategies to improve service quality and thus satisfy the needs of customers. A set of rules is derived from a large sample of airline customers, and its predictive ability is evaluated. The flow graph and the cause-and-effect relationship of the decision rules are heavily exploited in service quality characteristics. As compared with the results of other data-mining analyses, our results are encouraging. This study demonstrates that the combination of the RST model and flow graphs assists in identifying the needs of customers, determining their characteristics, and facilitating the development of an improvement strategy."