Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

Name: Rough Sets, Fuzzy Sets, Data Mining and Granular Computing | 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, Proceedings
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13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, Proceedings

Sergei O. Kuznetsov Dominik Slezak Daryl H. Hepting Boris G. Mirkin(Herausgeber*in)

Springer (Verlag)

Erschienen am 14. Juni 2011

XIII, 370 Seiten

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Inhalt

Title
Preface
Organization
Table of Contents
Invited Papers
Construction and Analysis of Web-Based Computer Science Information Networks
References
Towards Faster Estimation of Statistics and ODEs Under Interval, P-Box, and Fuzzy Uncertainty: From Interval Computations to Rough Set-Related Computations
Formulation of the Problem
Interval Computations: Brief Reminder
Rough Set Computations
Conclusions
References
Rough Set Based Uncertain Knowledge Expressing and Processing
Introduction of Uncertainty
Set Theory
Fuzzy Set Theory
Type-2 Fuzzy Set
Interval-Valued Fuzzy Set
Intuitionistic Fuzzy Set
Rough Set Theory
The Relationships of Fuzzy Set and Rough Set
Cloud Model
Set Pair Analysis
Interval Analysis
Extension Set
Future Directions and Topics of Rough Set Based Uncertain Knowledge Expressing and Processing
References
What is a Fuzzy Concept Lattice? II
Why Fuzzy Concepts?
Concepts in Formal Concept Analysis
Psychological Evidence
Fuzzy Logic as a Natural Choice
The Basic Approach
Basic Notions
Related Approaches
Mathematical Structures Behind
Closure Operators, Systems, and Galois Connections
Reduction to the Ordinary Case
Fuzzy Concept Lattice as a Lattice?
Some Further Issues Different from Ordinary Case
Formal Concepts as Maximal Rectangles
For Infinite Set of Truth Degrees, Fuzzy Concept Lattice over Finite Sets of Objects and Attributes May be Infinite
Reduction of a Fuzzy Context
Antitone vs. Isotone Galois Connections Induced by I
Further Issues
References
Rough Set Based Ensemble Classifier
References
Tutorial Papers
The Use of Rough Set Methods in Knowledge Discovery in Databases
References
Fuzzy-Rough Data Mining
Introduction
Fuzzy-Rough Feature Selection
Fuzzy-Rough Nearest Neighbour Classification
Hybrid Fuzzy Rule Induction
Instance Selection
Handling Missing Values
References
Rough Sets and Approximations
Dual Rough Approximations in Information Tables with Missing Values
Introduction
Rough Sets Under Complete Information
Methods of Possible Worlds
Methods of Possible Equivalence Classes
Conclusions
References
Rough Sets and General Basic Set Assignments
Introduction
Preliminaries
Pawlak Rough Sets
Extension of Pawlak Rough Sets
Rough Sets Based on General Basic Set Assignments
Binary Relations and General Basic Set Assignments
Conclusions
References
General Tool-Based Approximation Framework Based on Partial Approximation of Sets
Introduction
An Illustrative Example
Fundamentals of Partial Approximation of Sets
A General Tool-Based Approximation Framework
Applying General Framework to the Running Example
Conclusion
References
An Improved Variable Precision Model of Dominance-Based Rough Set Approach
Introduction
VC-DRSA and VP-DRSA
VC-DRSA
VP-DRSA
Inadequacies of VP-DRSA
Improved VP-DRSA Based on Inclusion Degree and Supported Degree (ISVP-DRSA)
Definitions and Properties of ISVP-DRSA
Illustrative Example
Conclusions
References
Rough Numbers and Rough Regression
Classical and Extended Models of Rough Numbers
Rough Calculations and Rough Regression
Experiments and Results
Conclusions and Further Works
References
Coverings and Granules
Covering Numbers in Covering-Based Rough Sets
Introduction
Basic Definitions
Covering Numbers
Definitions and Properties of Covering Numbers
Distance Established with Covering Numbers
Lattice Established with Covering Numbers
Conclusions
References
On Coverings of Rough Transformation Semigroups
Introduction and Preliminaries
Rough Finite State Machines
Rough Transformation Semigroups
Coverings
Conclusion
References
Covering Rough Set Model Based on Multi-granulations
Introduction
Preliminaries
Approximation Operators of CMGRS
Conclusion
References
A Descriptive Language Based on Granular Computing - Granular Logic
Introduction
Granulation in Real Sets and Related Operations
Real Granular Space
Indiscernibility Relation in R
Granular Logic
Syntax
Granular Mathematical Theorems in R
Perspective of Studying Granular Logic
References
Fuzzy Set Models
Optimization and Adaptation of Dynamic Models of Fuzzy Relational Cognitive Maps
Introduction
Dynamic Models of Fuzzy Relational Cognitive Maps
Fuzzyfication Parameters Optimization Problem
Adaptation Algorithm of the Relations Parameters
Selected Simulation Results
Model Building Assumptions
Parameters Adaptation of Individual Relations
Conclusions
References
Sensitivity Analysis for Fuzzy Linear Programming Problems
Introduction
Proposed Method
Numerical Examples
Conclusions
References
Estimation of Parameters of the Empirically Reconstructed Fuzzy Model of Measurements
Introduction
The Problem of Reduction and Reconstruction of the Model
Conclusions
References
Dominance-Based Rough Set Approach for Possibilistic Information Systems
Introduction
Review of Rough Set Theory and DRSA
DRSA for Possibilistic Information Systems
Preference-Ordered Possibilistic Information Systems
Fuzzy Dominance Relation
Dominance-Based Fuzzy Rough Approximations
Decision Rules
Conclusion
References
Creating Fuzzy Concepts: The One-Sided Threshold, Fuzzy Closure and Factor Analysis Methods
Introduction
Fuzzy Concept Lattice Creation and Fuzzy Factor Analysis
One-Sided Threshold Method
Fuzzy Closure Method
Fuzzy Factor Analysis Method
Experiments and Analysis of Results
Experimental Datasets
Threshold vs. Fuzzy Closure
Fuzzy Factor Analysis vs. Fuzzy Concept Lattice Creation
Conclusions and Future Work
References
Position Paper: Pragmatics in Fuzzy Theory
Fuzzy Theory and Formal Concept Analysis
Fuzzy Concepts
How Formal Concept Analysis Met Fuzzy Theory
Problems in Fuzzy Theory
Solutions and Hints
Representation of Fuzzyness by Distributed Objects
References
Fuzzy Set Applications
Regularization of Fuzzy Cognitive Maps for Hybrid Decision Support System
Introduction
Regularization
Neural Networks Regularization
Regularization of FCM
Interpretation of FCM Regularization
Hybrid Decision Support Model
Fuzzy Hierarchy Model
Fuzzy Cognitive Model
Integrated Model
Conclusion
References
On Designing of Flexible Neuro-Fuzzy Systems for Nonlinear Modelling
Introduction
Description of Neuro-Fuzzy System of a Mamdani Type
Neuro-Fuzzy Systems with Various Types of Triangular Norms
Designing and Learning of Neuro-Fuzzy Systems with Various Types of Triangular Norms
Evolution of Structure
Evolution of Parameters
Simulation Results
Chemical Plant Problem
HANG Problem
Conclusions
References
Time Series Processing and Forecasting Using Soft Computing Tools
Introduction
Discrete F-Transform and Its Matrix Representation
Fuzzy Partition and Its Matrix Representation
Discrete F-Transform
Time Series Decomposition
Models of Trend
Short Time Series Forecast
Express Analysis of Short Time Series and Web-service
Genetic Optimization
Conclusion
References
Fuzzy Linear Programming - Foreign Exchange Market
Introduction
Fuzzy Linear Programming
Foreign Exchange Market and Illustrative Example
Conclusion
References
Fuzzy Optimal Solution of Fuzzy Transportation Problems with Transshipments
Introduction
Proposed Method
Advantages of the Proposed Method
Results
Discussion
Conclusion
References
Fuzzy Optimal Solution of Fully Fuzzy Project Crashing Problems with New Representation of LR Flat Fuzzy Numbers
Introduction
JMD Representation of LR Flat Fuzzy Numbers
Mehar's Method with JMD LR Flat Fuzzy Numbers
Advantagesof JMD LR Flat Fuzzy Numbers
Results
Physical Interpretation of Results
Conclusion
References
A Prototype System for Rule Generation in Lipski's Incomplete Information Databases
Introduction
Rule Generation in DISs and NISs
Rule Generation in Incomplete Information Databases
An Example of an Incomplete Information Database
Non-deterministic Information and Missing Values
Information Incompleteness about Intervals and Derived DISs
Descriptors and Rule Generation in IIDs
Data Expression and Equivalence Classes
Execution for Table 1
Concluding Remarks
References
Compound Values
How to Reconstruct the System's Dynamics by Differentiating Interval-Valued and Set-Valued Functions
Formulation of the Problem
Case of Interval-Valued Functions
Fuzzy Case: Observation
General Multi-D Case
Conclusions
References
Symbolic Galois Lattices with Pattern Structures
Introduction
Symbolic Galois Lattices in Symbolic Data Analysis
Pattern Concept Lattices
Symbolic Galois Lattices with Pattern Structures
Handling Heterogeneous Variables with Pattern Structures
Handling Missing Values
Links with Conceptual Scaling
Conclusion
References
Multiargument Relationships in Fuzzy Databases with Attributes Represented by Interval-Valued Possibility Distributions
Introduction
Interval-Valued possibility distributions
Functional Dependencies in Fuzzy Databases
Fuzzy Multiargument Relationships
Conclusions
References
Disjunctive Set-Valued Ordered Information Systems Based on Variable Precision Dominance Relation
Introduction
Rough Set Model Based on Variable Precision Dominance Relation
Attribute Reduction in Disjunctive SvOIS
Conclusion
References
An Interval-Valued Fuzzy Soft Set Approach for Normal Parameter Reduction
Introduction
Essential Rudiments
Normal Parameter Reduction of Interval-Valued Fuzzy Soft Sets
Conclusion
References
Feature Selection and Reduction
Incorporating Game Theory in Feature Selection for Text Categorization
Introduction
Feature Selection in High Class Imbalance
Feature Selection with Game Theory
A Demonstrative Example
Conclusion
References
Attribute Reduction in Random Information Systems with Fuzzy Decisions
Introduction
Fuzzy Evidence Theory Induced by a Crisp Belief Structure
Random Information Systems with Fuzzy Decisions and Rough Fuzzy Approximations
Attribute Reducts in Random Information Systems with Fuzzy Decisions
Conclusion
References
Discernibility-Matrix Method Based on the Hybrid of Equivalence and Dominance Relations
Introduction
Basic Concepts in Dominance-Based Rough Set Approach
Dominance-Equivalence Relation and DM Method
Equivalence-Dominance Relation and DM Method
Conclusion
References
Studies on an Effective Algorithm to Reduce the Decision Matrix
Consideration on the Decision Matrix
Consideration on Reducing Eq. (1)
Consideration on Reducing Eq. (2)
An Effective Algorithm to Reduce the Decision Matrix
Simulation Experiment - Comparison of the Execution Time with Existing Software
References
Accumulated Cost Based Test-Cost-Sensitive Attribute Reduction
Introduction
Problem Definition
Accumulated Cost Based Heuristic Function
Experiments
Running Examples
Results
Conclusions
References
Clusters and Concepts
Approximate Bicluster and Tricluster Boxes in the Analysis of Binary Data
Introduction
The Notions of Formal Concept and Box Clustering
Locally Optimal Box Cluster
Extending to Triclusters and P-Clusters
Experiments
Conclusion
References
From Triconcepts to Triclusters
Introduction
Main Definitions
Mining Dense Triclusters
Prime, Double Prime and Box Operators of 1-Sets
An Algorithm: TRICL
Real Data and Experiments
Conclusion
References
Learning Inverted Dirichlet Mixtures for Positive Data Clustering
Introduction
The Inverted Dirichlet Mixture Model
Experimental Results
Synthetic Data
Real Data
Conclusion
References
Developing Additive Spectral Approach to Fuzzy Clustering
References
Rules and Trees
Data-Driven Adaptive Selection of Rules Quality Measures for Improving the Rules Induction Algorithm
Introduction
Rule Quality Measures
Data-Driven Selection of Rules Quality Measures in Rules Induction Algorithm
Experiments
Conclusions
References
Relationships between Depth and Number of Misclassifications for Decision Trees
Introduction
Basic Notions
Representation of Sets of Decision Trees
Relationships between Depth and Number of Misclassifications
Experimental Results
Lymphography
Breast-Cancer
Tic-Tac-Toe
Conclusions
References
Dynamic Successive Feed-Forward Neural Network for Learning Fuzzy Decision Tree
Introduction
Methodology and Simulation Design
Simple Neural Network Architecture
Representation of Decision Tree over Neural Network
Experiments and Results
Feed-Forward Neural Network
Fuzzy Decision Tree over Feed Forward Neural Network
Conclusion
References
An Improvement for Fast-Flux Service Networks Detection Based on Data Mining Techniques
Introduction
Characteristics of FFSN
Num_asn
Num_cname
Num_ns
Num_address
TTL (Time-To-Live)
Rate_flux
The Approach
Experiments and Analysis
Conclusion
References
Online Learning Algorithm for Ensemble of Decision Rules
Introduction
Decision Tables and -Decision Rules
Initial Classifier
Online Algorithm
Conclusions
References
Image Processing
Automatic Image Annotation Based on Low-Level Features and Classification of the Statistical Classes
Introduction
Low-Level Image Features
Statistical Classes Classification
Notion of Statistical Class
Secondary Features Construction Based on Inclusion Measures
The Aggregation of Secondary Features
Conclusion
References
Machine Learning Methods in Character Recognition
Introduction
ABBYY OCR Technologies Recognition Schema
Requirements Imposed on Classifiers by Recognition Schema
Modifications of Classical Algorithms
Modifications of Decision Tree Classifier
Experimentation
Decision Tree Construction Method
Decision Tree Hypotheses Generation
Recognition Rate Comparison
Ability to Organize Cut-Offs Efficiently
Conclusion
References
A Liouville-Based Approach for Discrete Data Categorization
Introduction
The Smoothing Model
Background
The Model
Model Learning
Experimental Results
Conclusion
References
Image Recognition with a Large Database Using Method of Directed Enumeration Alternatives Modification
Introduction
MDEA Modification
Experimental Results
Conclusion
References
Interactions and Visualisation
Comparators for Compound Object Identification
Introduction
Data Segmentation
Image Granulation
Area Identification
Example and Results
Conclusions
References
Measuring Implicit Attitudes in Human-Computer Interactions
Introduction
Hypothesis
Presenter Agent Experiment
Results
Revised IAT Procedure and Scoring Algorithm
Conclusions and Future Work
Summary
References
Visualization of Semantic Network Fragments Using Multistripe Layout
Introduction
The Object of Visualization
Multistripe Layout
Layout Extension
Conclusion
References
Pawlak Collaboration Graph and Its Properties
Introduction
Pawlak Collaboration Graph
Basic Analysis of Pawlak Collaboration Graph
Conclusions and Future Work
References
Author Index

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