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      1. Data och IT
      2. Systemvetenskap och AI
      3. Artificiell intelligens

      Rough Sets and Knowledge Technology

      Second International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007, Proceedings

      AvJingTao Yao,Pawan Lingras

      Häftad, Engelska, 2007

      Del i serien Lecture Notes in Computer Science

      574 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      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.

      Produktinformation

      • Utgivningsdatum:2007-04-27
      • Mått:155 x 235 x 32 mm
      • Vikt:890 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Lecture Notes in Computer Science
      • Antal sidor:578
      • Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
      • ISBN:9783540724575

      Utforska kategorier

      • Artificiell intelligens inom Data och IT

      Innehållsförteckning

      • Invited Papers.- Decision-Theoretic Rough Set Models.- Efficient Attribute Reduction Based on Discernibility Matrix.- Near Sets. Toward Approximation Space-Based Object Recognition.- Rough Set Foundations.- On Covering Rough Sets.- On Transitive Uncertainty Mappings.- A Complete Method to Incomplete Information Systems.- Information Concept Lattice and Its Reductions.- Homomorphisms Between Relation Information Systems.- Dynamic Reduction Based on Rough Sets in Incomplete Decision Systems.- Entropies and Co–entropies for Incomplete Information Systems.- Granular Computing Based on a Generalized Approximation Space.- A General Definition of an Attribute Reduct.- Multiple Criteria Decision Analysis.- Mining Associations for Interface Design.- Optimized Generalized Decision in Dominance-Based Rough Set Approach.- Monotonic Variable Consistency Rough Set Approaches.- Bayesian Decision Theory for Dominance-Based Rough Set Approach.- Ranking by Rough Approximation of Preferences for Decision Engineering Applications.- Applying a Decision Making Model in the Early Diagnosis of Alzheimer’s Disease.- Biometrics.- Singular and Principal Subspace of Signal Information System by BROM Algorithm.- Biometric Verification by Projections in Error Subspaces.- Absolute Contrasts in Face Detection with AdaBoost Cascade.- Voice Activity Detection for Speaker Verification Systems.- Face Detection by Discrete Gabor Jets and Reference Graph of Fiducial Points.- Iris Recognition with Adaptive Coding.- Kansei Engineering.- Overview of Kansei System and Related Problems.- Reduction of Categorical and Numerical Attribute Values for Understandability of Data and Rules.- Semi-structured Decision Rules in Object-Oriented Rough Set Models for Kansei Engineering.- Functional Data Analysis and ItsApplication.- Evaluation of Pictogram Using Rough Sets.- A Logical Representation of Images by Means of Multi-rough Sets for Kansei Image Retrieval.- Autonomy-Oriented Computing.- A Batch Rival Penalized EM Algorithm for Gaussian Mixture Clustering with Automatic Model Selection.- A Memetic-Clustering-Based Evolution Strategy for Traveling Salesman Problems.- An Efficient Probabilistic Approach to Network Community Mining.- A New Approach to Underdetermined Blind Source Separation Using Sparse Representation.- Soft Computing in Bioinformatics.- Evolutionary Fuzzy Biclustering of Gene Expression Data.- Rough Clustering and Regression Analysis.- Rule Induction for Prediction of MHC II-Binding Peptides.- Efficient Local Protein Structure Prediction.- Roughfication of Numeric Decision Tables: The Case Study of Gene Expression Data.- Ubiquitous Computing and Networking.- Ubiquitous Customer Relationship Management (uCRM).- Towards the Optimal Design of an RFID-Based Positioning System for the Ubiquitous Computing Environment.- Wave Dissemination for Wireless Sensor Networks.- Two Types of a Zone-Based Clustering Method for Wireless Sensor Networks.- Rough Set Algorithms.- Set Approximations in Multi-level Conceptual Data.- Knowledge Reduction in Generalized Consistent Decision Formal Contexts.- Graphical Representation of Information on the Set of Reducts.- Minimal Attribute Space Bias for Attribute Reduction.- Two-Phase ?-Certain Reducts Generation.- Formal Concept Analysis and Set-Valued Information Systems.- Descriptors and Templates in Relational Information Systems.- ROSA: An Algebra for Rough Spatial Objects in Databases.- Knowledge Representation and Reasoning.- Learning Models Based on Formal Concept.- Granulation Based Approximate Ontologies Capture.- Fuzzy-ValuedTransitive Inclusion Measure, Similarity Measure and Application to Approximate Reasoning.- Model Composition in Multi-dimensional Data Spaces.- An Incremental Approach for Attribute Reduction in Concept Lattice.- Topological Space for Attributes Set of a Formal Context.- Flow Graphs as a Tool for Mining Prediction Rules of Changes of Components in Temporal Information Systems.- Approximation Space-Based Socio-Technical Conflict Model.- Genetic Algorithms.- Improved Quantum-Inspired Genetic Algorithm Based Time-Frequency Analysis of Radar Emitter Signals.- Parameter Setting of Quantum-Inspired Genetic Algorithm Based on Real Observation.- A Rough Set Penalty Function for Marriage Selection in Multiple-Evaluation Genetic Algorithms.- Multiple Solutions by Means of Genetic Programming: A Collision Avoidance Example.- Rough Set Applications.- An Approach for Selective Ensemble Feature Selection Based on Rough Set Theory.- Using Rough Reducts to Analyze the Independency of Earthquake Precursory Items.- Examination of the Parameter Space of a Computational Model of Acute Ischaemic Stroke Using Rough Sets.- Using Rough Set Theory to Induce Pavement Maintenance and Rehabilitation Strategy.- Descent Rules for Championships.- Rough Neuro Voting System for Data Mining: Application to Stock Price Prediction.- Counting All Common Subsequences to Order Alternatives.
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