Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing : 10th International Conference, RSFDGrC 2005, Regina, Canada, August 31 - September 3, 2005, Proceedings, Part I / edited by Dominik Slezak, Marcin Szczuka, Ivo Duentsch, Yiyu Yao.

Format:

Book

Contributor:

Ślęzak, Dominik, editor.

Szczuka, Marcin, editor.

Duentsch, Ivo, editor.

Yao, Yiyu, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 3641.

Lecture Notes in Artificial Intelligence ; 3641

Language:

English

Subjects (All):

Artificial intelligence.

Information storage and retrieval.

Database management.

Logic, Symbolic and mathematical.

Computers.

Pattern perception.

Artificial Intelligence.

Information Storage and Retrieval.

Database Management.

Mathematical Logic and Formal Languages.

Computation by Abstract Devices.

Pattern Recognition.

Local Subjects:

Artificial Intelligence.

Information Storage and Retrieval.

Database Management.

Mathematical Logic and Formal Languages.

Computation by Abstract Devices.

Pattern Recognition.

Physical Description:

1 online resource (XXIV, 748 pages).

Edition:

First edition 2005.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.

System Details:

text file PDF

Summary:

This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st-September 3rd, 2005. This conference followed in the footsteps of inter- tional events devoted to the subject of rough sets, held so far in Canada, China, Japan,Poland,Sweden, and the USA. RSFDGrC achievedthe status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signi?cant results in many areas such as ?nance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications. In the case of this event, additional e?ort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas.

Contents:

Invited Papers

Rough Sets and Flow Graphs

A Modal Characterization of Indiscernibility and Similarity Relations in Pawlak's Information Systems

Granular Computing with Shadowed Sets

Rough Set Approximations

Rough Sets and Higher Order Vagueness

Approximation in Formal Concept Analysis

Second-Order Rough Approximations in Multi-criteria Classification with Imprecise Evaluations and Assignments

New Approach for Basic Rough Set Concepts

A Partitional View of Concept Lattice

Characterizations of Attributes in Generalized Approximation Representation Spaces

Rough-Algebraic Foundations

Proximity Spaces of Exact Sets

Rough Group, Rough Subgroup and Their Properties

Concept Lattices vs. Approximation Spaces

Rough Sets over the Boolean Algebras

Algebraic Approach to Generalized Rough Sets

Logic for Rough Sets with Rough Double Stone Algebraic Semantics

Feature Selection and Reduction

On Partial Tests and Partial Reducts for Decision Tables

The Second Attribute

Pairwise Cores in Information Systems

Data Preprocessing and Kappa Coefficient

Incremental Attribute Reduction Based on Elementary Sets

Finding Rough Set Reducts with SAT

Feature Selection with Adjustable Criteria

Feature Selection Based on Relative Attribute Dependency: An Experimental Study

Reasoning in Information Systems

On Consistent and Partially Consistent Extensions of Information Systems

A New Treatment and Viewpoint of Information Tables

Incomplete Data and Generalization of Indiscernibility Relation, Definability, and Approximations

Discernibility Functions and Minimal Rules in Non-deterministic Information Systems

Studies on Rough Sets in Multiple Tables

Normalization in a Rough Relational Database

Rough-Probabilistic Approaches

Probabilistic Rough Sets

Variable Precision Bayesian Rough Set Model and Its Application to Human Evaluation Data

Variable Precision Rough Set Approach to Multiple Decision Tables

Rough Membership and Bayesian Confirmation Measures for Parameterized Rough Sets

Rough Sets Handling Missing Values Probabilistically Interpreted

The Computational Complexity of Inference Using Rough Set Flow Graphs

Rough-Fuzzy Hybridization

Upper and Lower Probabilities of Fuzzy Events Induced by a Fuzzy Set-Valued Mapping

Variable Precision Fuzzy Rough Sets Model in the Analysis of Process Data

CRST: A Generalization of Rough Set Theory

An Extension of Rough Approximation Quality to Fuzzy Classification

Fuzzy Rules Generation Method for Classification Problems Using Rough Sets and Genetic Algorithms

Multilayer FLC Design Based on RST

Fuzzy Methods in Data Analysis

Interpretable Rule Extraction and Function Approximation from Numerical Input/Output Data Using the Modified Fuzzy TSK Model, TaSe Model

A New Feature Weighted Fuzzy Clustering Algorithm

User-Driven Fuzzy Clustering: On the Road to Semantic Classification

Evolutionary Computing

Research on Clone Mind Evolution Algorithm

A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms

Finding Minimal Rough Set Reducts with Particle Swarm Optimization

MEA Based Nonlinearity Correction Algorithm for the VCO of LFMCW Radar Level Gauge

Machine Learning

On Degree of Dependence Based on Contingency Matrix

Model Selection and Assessment for Classification Using Validation

Dependency Bagging

Combination of Metric-Based and Rule-Based Classification

Combining Classifiers Based on OWA Operators with an Application to Word Sense Disambiguation

System Health Prognostic Model Using Rough Sets

Approximate and Uncertain Reasoning

Live Logic TM : Method for Approximate Knowledge Discovery and Decision Making

Similarity, Approximations and Vagueness

Decision Theory = Performance Measure Theory + Uncertainty Theory

Probabilistic Network Models

The Graph-Theoretical Properties of Partitions and Information Entropy

A Comparative Evaluation of Rough Sets and Probabilistic Network Algorithms on Learning Pseudo-independent Domains

On the Complexity of Probabilistic Inference in Singly Connected Bayesian Networks

Spatial and Temporal Reasoning

Representing the Process Semantics in the Situation Calculus

Modeling and Refining Directional Relations Based on Fuzzy Mathematical Morphology

A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records

Hierarchical Information Maps

Non-standard Logics

Ordered Belief Fusion in Possibilistic Logic

Description of Fuzzy First-Order Modal Logic Based on Constant Domain Semantics

Arrow Decision Logic

Transforming Information Systems

A Discrete Event Control Based on EVALPSN Stable Model Computation

Granular Computing

Tolerance Relation Based Granular Space

Discernibility-Based Variable Granularity and Kansei Representations

Rough Set Approximation Based on Dynamic Granulation

Granular Logic with Closeness Relation and Its Reasoning

Ontological Framework for Approximation

Table Representations of Granulations Revisited.

Other Format:

Printed edition:

ISBN:

978-3-540-31825-5

9783540318255

Access Restriction:

Restricted for use by site license.