Rough Sets and Current Trends in Computing

6th International Conference, RSCTC 2008 Akron, OH, USA, October 23 - 25, 2008 Proceedings
Herausgegeben:Chan, Chien-Chung; Grzymala-Busse, Jerzy W.; Ziarko, Wojciech P.

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2008, held in Akron, OH, USA, in October 2008.

The 49 revised full papers presented together with 2 keynote papers and 3 special session papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on logical and mathematical foundations, data analysis, data mining, decision support systems, clustering, pattern recognition and image processing, as well as bioinformatics. The three special session papers cover topics such as rough sets in data warehousing, classification challenges in email archiving, and approximation theories: granular computing vs. rough sets.

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The articles in this volume were selected for presentation at the Sixth Inter- tional Conference on Rough Sets and Current Trends in Computing (RSCTC 2008), which took place on October 23-25 in Akron, Ohio, USA. The conference is a premier event for researchersand industrial professionals interested in the theory and applications of rough sets and related methodo- gies. Since its introduction over 25 years ago by Zdzislaw Pawlak, the theory of rough sets has grown internationally and matured, leading to novel applications and theoretical works in areas such as data mining and knowledge discovery, machine learning, neural nets, granular and soft computing, Web intelligence, pattern recognition and control. The proceedings of the conferences in this - ries, as well as in Rough Sets and Knowledge Technology (RSKT), and the Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC) series report a variety of innovative applications of rough set theory and of its extensions.Since its inception, the mathematical rough set theory was closely connected to application ?elds of computer science and to other areas, such as medicine, which provided additional motivation for its further development and tested its real-life value. Consequently, rough set conferences emphasize the - teractionsandinterconnectionswith relatedresearchareas,providingforumsfor exchanging ideas and mutual learning. The latter aspect is particularly imp- tant since the development of rough set-related applications usually requires a combination of often diverse expertise in rough sets and an application ?eld.

Produktdetails

• Lecture Notes in Computer Science 5306
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 12538836, 978-3-540-88423-1
• 2008
• Seitenzahl: 548
• Erscheinungstermin: 7. Oktober 2008
• Englisch
• Abmessung: 235mm x 155mm x 30mm
• Gewicht: 819g
• ISBN-13: 9783540884231
• ISBN-10: 3540884238
• Artikelnr.: 25396053

Inhaltsangabe

Keynote Papers.- Neuroeconomics: Yet Another Field Where Rough Sets Can Be Useful?.- Research Directions in the KES Centre.- Logical and Mathematical Foundations.- On Irreducible Descriptive Sets of Attributes for Information Systems.- Dominance-Based Rough Set Approach and Bipolar Abstract Rough Approximation Spaces.- Paraconsistent Logic Programs with Four-Valued Rough Sets.- An Equivalent Definition of Rough Sets.- A Note on Attribute Reduction in the Decision-Theoretic Rough Set Model.- An Interpretation of Belief Functions on Infinite Universes in the Theory of Rough Sets.- Some Remarks on Approximations of Arbitrary Binary Relations by Partial Orders.- On Rough Equalities and Rough Equivalences of Sets.- Data Analysis.- Statistical Independence of Multi-variables from the Viewpoint of Linear Algebra.- Rough Mereology in Classification of Data: Voting by Means of Residual Rough Inclusions.- Rough Set Approach to Information Tables with Imprecise Decisions.- Computing Approximations of Dominance-Based Rough Sets by Bit-Vector Encodings.- A Framework for Multiagent Mobile Robotics: Spatial Reasoning Based on Rough Mereology in Player/Stage System.- Natural versus Granular Computing: Classifiers from Granular Structures.- Data Mining.- Inducing Better Rule Sets by Adding Missing Attribute Values.- Rule Induction: Combining Rough Set and Statistical Approaches.- Action Rules Discovery without Pre-existing Classification Rules.- Hierarchical Learning in Classification of Structured Objects.- A Comparison of the LERS Classification System and Rule Management in PRSM.- Similarity Relation in Classification Problems.- Probabilistic Granule Analysis.- Paraconsistent Case-Based Reasoning Applied to a Restoration of Electrical Power Substations.- Solving the Attribute Reduction Problem with Ant Colony Optimization.- Actor Critic Learning: A Near Set Approach.- Compact Rule Learner on Weighted Fuzzy Approximation Spaces for Class Imbalanced and Hybrid Data.- Feature Selection Based on the Rough Set Theory and Expectation-Maximization Clustering Algorithm.- Outlier Detection Based on Granular Computing.- Implementing a Rule Generation Method Based on Secondary Differences of Two Criteria.- Lower and Upper Approximations of Rules in Non-deterministic Information Systems.- A New Approach to Fuzzy-Rough Nearest Neighbour Classification.- Decision Support Systems.- Towards Approximation of Risk.- Business Aviation Decision-Making Using Rough Sets.- Phase Transition in SONFIS and SORST.- A New Rough Sets Decision Method Based on PCA and Ordinal Regression.- Rough Set Flow Graphs and Max???* Fuzzy Relation Equations in State Prediction Problems.- Clustering.- Precision of Rough Set Clustering.- A Dynamic Approach to Rough Clustering.- Learning Patterns from Clusters Using Reduct.- Pattern Recognition and Image Processing.- Experiments with Rough Set Approach to Face Recognition.- Standard and Fuzzy Rough Entropy Clustering Algorithms in Image Segmentation.- Efficient Mining of Jumping Emerging Patterns with Occurrence Counts for Classification.- Evolutionary Algorithm for Fingerprint Images Filtration.- Efficient Discovery of Top-K Minimal Jumping Emerging Patterns.- Hierarchical Tree for Dissemination of Polyphonic Noise.- A Data Driven Emotion Recognition Method Based on Rough Set Theory.- Learning from Soft-Computing Methods on Abnormalities in Audio Data.- Bioinformatics.- Shadowed Clustering for Speech Data and Medical Image Segmentation.- Computational Intelligence Techniques Applied to Magnetic Resonance Spectroscopy Data of HumanBrain Cancers.- A Hybrid Model for Aiding in Decision Making for the Neuropsychological Diagnosis of Alzheimer's Disease.- Special Sessions.- Rough Sets in Data Warehousing.- Classification Challenges in Email Archiving.- Approximation Theories: Granular Computing vs Rough Sets.