Rough Sets and Knowledge Technology: First International Conference, Rskt 2006, Chongquing, China, July 24-26, 2006, Proceedings by James F. PetersRough Sets and Knowledge Technology: First International Conference, Rskt 2006, Chongquing, China, July 24-26, 2006, Proceedings by James F. Peters

Rough Sets and Knowledge Technology: First International Conference, Rskt 2006, Chongquing, China…

byJames F. PetersEditorYiju Yao

Paperback | July 6, 2006

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This volume contains the papers selected for presentation at the First Int- national Conference on Rough Sets and Knowledge Technology (RSKT 2006) organized in Chongqing, P. R. China, July 24-26, 2003. There were 503 s- missions for RSKT 2006 except for 1 commemorative paper, 4 keynote papers and 10 plenary papers. Except for the 15 commemorative and invited papers, 101 papers were accepted by RSKT 2006 and are included in this volume. The acceptance rate was only 20%. These papers were divided into 43 regular oral presentation papers (each allotted 8 pages), and 58 short oral presentation - pers (each allotted 6 pages) on the basis of reviewer evaluation. Each paper was reviewed by two to four referees. Since the introduction of rough sets in 1981 by Zdzis law Pawlak, many great advances in both the theory and applications have been introduced. Rough set theory is closely related to knowledge technology in a variety of forms such as knowledge discovery, approximate reasoning, intelligent and multiagent systems design, and knowledge intensive computations that signal the emergence of a knowledge technology age. The essence of growth in cutting-edge, state-of-t- art and promising knowledge technologies is closely related to learning, pattern recognition,machine intelligence and automation of acquisition, transformation, communication, exploration and exploitation of knowledge. A principal thrust of such technologies is the utilization of methodologies that facilitate knowledge processing.
Title:Rough Sets and Knowledge Technology: First International Conference, Rskt 2006, Chongquing, China…Format:PaperbackDimensions:810 pages, 23.5 × 15.5 × 0.07 inPublished:July 6, 2006Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3540362975

ISBN - 13:9783540362975

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Table of Contents

Commemorative Paper.- Some Contributions by Zdzis?aw Pawlak.- Keynote Papers.- Conflicts and Negotations.- Hierarchical Machine Learning - A Learning Methodology Inspired by Human Intelligence.- Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation.- Towards Network Autonomy.- Plenary Papers.- A Roadmap from Rough Set Theory to Granular Computing.- Partition Dependencies in Hierarchies of Probabilistic Decision Tables.- Knowledge Theory and Artificial Intelligence.- Applications of Knowledge Technologies to Sound and Vision Engineering.- A Rough Set Approach to Data with Missing Attribute Values.- Cognitive Neuroscience and Web Intelligence.- Cognitive Informatics and Contemporary Mathematics for Knowledge Manipulation.- Rough Mereological Reasoning in Rough Set Theory: Recent Results and Problems.- Theoretical Study of Granular Computing.- Knowledge Discovery by Relation Approximation: A Rough Set Approach.- Rough Computing.- Reduction-Based Approaches Towards Constructing Galois (Concept) Lattices.- A New Discernibility Matrix and Function.- The Relationships Between Variable Precision Value and Knowledge Reduction Based on Variable Precision Rough Sets Model.- On Axiomatic Characterization of Approximation Operators Based on Atomic Boolean Algebras.- Rough Set Attribute Reduction in Decision Systems.- A New Extension Model of Rough Sets Under Incomplete Information.- Applying Rough Sets to Data Tables Containing Possibilistic Information.- Redundant Data Processing Based on Rough-Fuzzy Approach.- Further Study of the Fuzzy Reasoning Based on Propositional Modal Logic.- The M-Relative Reduct Problem.- Rough Contexts and Rough-Valued Contexts.- Combination Entropy and Combination Granulation in Incomplete Information System.- An Extension of Pawlak's Flow Graphs.- Rough Sets and Brouwer-Zadeh Lattices.- Covering-Based Generalized Rough Fuzzy Sets.- Axiomatic Systems of Generalized Rough Sets.- Rough-Sets-Based Combustion Status Diagnosis.- Research on System Uncertainty Measures Based on Rough Set Theory.- Conflict Analysis and Information Systems: A Rough Set Approach.- A Novel Discretizer for Knowledge Discovery Approaches Based on Rough Sets.- Function S-Rough Sets and Recognition of Financial Risk Laws.- Knowledge Reduction in Incomplete Information Systems Based on Dempster-Shafer Theory of Evidence.- Decision Rules Extraction Strategy Based on Bit Coded Discernibility Matrix.- Attribute Set Dependence in Apriori-Like Reduct Computation.- Some Methodological Remarks About Categorical Equivalences in the Abstract Approach to Roughness - Part I.- Some Methodological Remarks About Categorical Equivalences in the Abstract Approach to Roughness - Part II.- Lower Bounds on Minimal Weight of Partial Reducts and Partial Decision Rules.- On Reduct Construction Algorithms.- Association Reducts: Boolean Representation.- Notes on Rough Sets and Formal Concepts.- Evolutionary Computing.- High Dimension Complex Functions Optimization Using Adaptive Particle Swarm Optimizer.- Adaptive Velocity Threshold Particle Swarm Optimization.- Fuzzy Sets.- Relationship Between Inclusion Measure and Entropy of Fuzzy Sets.- A General Model for Transforming Vague Sets into Fuzzy Sets.- An Iterative Method for Quasi-Variational-Like Inclusions with Fuzzy Mappings.- Granular Computing.- Application of Granular Computing in Knowledge Reduction.- Advances in the Quotient Space Theory and Its Applications.- The Measures Relationships Study of Three Soft Rules Based on Granular Computing.- Neural Computing.- A Generalized Neural Network Architecture Based on Distributed Signal Processing.- Worm Harm Prediction Based on Segment Procedure Neural Networks.- Accidental Wow Defect Evaluation Using Sinusoidal Analysis Enhanced by Artificial Neural Networks.- A Constructive Algorithm for Training Heterogeneous Neural Network Ensemble.- Machine Learning and KDD.- Gene Regulatory Network Construction Using Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM).- Mining Biologically Significant Co-regulation Patterns from Microarray Data.- Fast Algorithm for Mining Global Frequent Itemsets Based on Distributed Database.- A VPRSM Based Approach for Inducing Decision Trees.- Differential Evolution Fuzzy Clustering Algorithm Based on Kernel Methods.- Classification Rule Mining Based on Particle Swarm Optimization.- A Bottom-Up Distance-Based Index Tree for Metric Space.- Subsequence Similarity Search Under Time Shifting.- Developing a Rule Evaluation Support Method Based on Objective Indices.- Data Dimension Reduction Using Rough Sets for Support Vector Classifier.- A Comparison of Three Graph Partitioning Based Methods for Consensus Clustering.- Feature Selection, Rule Extraction, and Score Model: Making ATC Competitive with SVM.- Relevant Attribute Discovery in High Dimensional Data: Application to Breast Cancer Gene Expressions.- Credit Risk Evaluation with Least Square Support Vector Machine.- The Research of Sampling for Mining Frequent Itemsets.- ECPIA: An Email-Centric Personal Intelligent Assistant.- A Novel Fuzzy C-Means Clustering Algorithm.- Document Clustering Based on Modified Artificial Immune Network.- A Novel Approach to Attribute Reduction in Concept Lattices.- Granule Sets Based Bilevel Decision Model.- An Enhanced Support Vector Machine Model for Intrusion Detection.- A Modified K-Means Clustering with a Density-Sensitive Distance Metric.- Swarm Intelligent Tuning of One-Class ?-SVM Parameters.- A Generalized Competitive Learning Algorithm on Gaussian Mixture with Automatic Model Selection.- The Generalization Performance of Learning Machine with NA Dependent Sequence.- Using RS and SVM to Detect New Malicious Executable Codes.- Applying PSO in Finding Useful Features.- Logics and Reasoning.- Generalized T-norm and Fractional "AND" Operation Model.- Improved Propositional Extension Rule.- Web Services-Based Digital Library as a CSCL Space Using Case-Based Reasoning.- Using Description Logic to Determine Seniority Among RB-RBAC Authorization Rules.- The Rough Logic and Roughness of Logical Theories.- Multiagent Systems and Web Intelligence.- Research on Multi-Agent Service Bundle Middleware for Smart Space.- A Customized Architecture for Integrating Agent Oriented Methodologies.- A New Method for Focused Crawler Cross Tunnel.- Migration of the Semantic Web Technologies into E-Learning Knowledge Management.- Opponent Learning for Multi-agent System Simulation.- Pattern Recognition.- A Video Shot Boundary Detection Algorithm Based on Feature Tracking.- Curvelet Transform for Image Authentication.- An Image Segmentation Algorithm for Densely Packed Rock Fragments of Uneven Illumination.- A New Chaos-Based Encryption Method for Color Image.- Support Vector Machines Based Image Interpolation Correction Scheme.- Pavement Distress Image Automatic Classification Based on DENSITY-Based Neural Network.- Towards Fuzzy Ontology Handling Vagueness of Natural Languages.- Evoked Potentials Estimation in Brain-Computer Interface Using Support Vector Machine.- Intra-pulse Modulation Recognition of Advanced Radar Emitter Signals Using Intelligent Recognition Method.- Multi-objective Blind Image Fusion.- System Engineering and Description.- The Design of Biopathway's Modelling and Simulation System Based on Petri Net.- Timed Hierarchical Object-Oriented Petri Net-Part I: Basic Concepts and Reachability Analysis.- Approximate Semantic Query Based on Multi-agent Systems.- Real-Life Applications Based on Knowledge Technology.- Swarm Intelligent Analysis of Independent Component and Its Application in Fault Detection and Diagnosis.- Using VPRS to Mine the Significance of Risk Factors in IT Project Management.- Mining of MicroRNA Expression Data-A Rough Set Approach.- Classifying Email Using Variable Precision Rough Set Approach.- Facial Expression Recognition Based on Rough Set Theory and SVM.- Gene Selection Using Rough Set Theory.- Attribute Reduction Based Expected Outputs Generation for Statistical Software Testing.- FADS: A Fuzzy Anomaly Detection System.- Gene Selection Using Gaussian Kernel Support Vector Machine Based Recursive Feature Elimination with Adaptive Kernel Width Strategy.