Transactions on Rough Sets VII

Klappentext
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume VII of the Transactions on Rough Sets (TRS) series is a sequel to volume VI of the TRS. Both volumes commemorate the life and work of Zdzislaw Pawlak (1926-2006). His legacy is rich and varied. Prof. Pawlak's research contributions have had far-reaching implications inasmuch as his works have been fundamental in establishing new perspectives for scientific research in a wide spectrum of fields. This volume of the TRS series presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak. In particular, it introduces a number of advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science. These advances have significant implications in a number of research areas such as the foundations of rough sets, approximate reasoning, bioinformatics, computational intelligence, cognitive science, data mining, information systems, intelligent systems, machine intelligence, and security.

Inhalt
Contributed Papers.- Speech Coding Employing Intelligent Signal Processing Techniques.- Relational Attribute Systems II: Reasoning with Relations in Information Structures.- Dominance-Based Rough Set Approach as a Proper Way of Handling Graduality in Rough Set Theory.- Deriving Belief Networks and Belief Rules from Data: A Progress Report.- Selection of Important Attributes for Medical Diagnosis Systems.- Using Approximate Reduct and LVQ in Case Generation for CBR Classifiers.- Mining Rough Association from Text Documents for Web Information Gathering.- Applications of Rough Set Based K-Means, Kohonen SOM, GA Clustering.- Characterizing Pawlak's Approximation Operators.- Application of Rough Sets in Pattern Recognition.- Lower and Upper Approximations in Data Tables Containing Possibilistic Information.- Hybrid Rough Sets-Population Based System.- Hybrid Rough Sets Intelligent System Architecture for Survival Analysis.- Rough Sets in Bioinformatics.- Rough Feature Selection for Intelligent Classifiers.- Granulation as a Privacy Protection Mechanism.- A Note on Definability and Approximations.- Feature Selection in Audiovisual Emotion Recognition Based on Rough Set Theory.- Monographs.- Novel Classification and Segmentation Techniques with Application to Remotely Sensed Images.