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Rough Sets and Current Trends in Computing

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Cover of 'Rough Sets and Current Trends in Computing'

Table of Contents

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    Book Overview
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    Chapter 1 In Pursuit of Patterns in Data Reasoning from Data - The Rough Set Way
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    Chapter 2 Toward a Theory of Hierarchical Definability (THD)
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    Chapter 3 Modelling Biological Phenomena with Rough Sets
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    Chapter 4 Database Mining on Derived Attributes Granular and Rough Computing Approach
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    Chapter 5 A Proposed Evolutionary, Self-Organizing Automaton for the Control of Dynamic Systems
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    Chapter 6 Rough Set Analysis of Preference-Ordered Data
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    Chapter 7 Fuzzy Sets, Multi-valued Mappings, and Rough Sets
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    Chapter 8 Investigating the Choice of l and u Values in the Extended Variable Precision Rough Sets Model
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    Chapter 9 A Quantitative Analysis of Preclusivity vs. Similarity Based Rough Approximations
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    Chapter 10 Heyting Wajsberg Algebras as an Abstract Environment Linking Fuzzy and Rough Sets
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    Chapter 11 Dominance-Based Rough Set Approach Using Possibility and Necessity Measures
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    Chapter 12 Generalized Decision Algorithms, Rough Inference Rules, and Flow Graphs
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    Chapter 13 Generalized Rough Sets and Rule Extraction
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    Chapter 14 Towards a Mereological System for Direct Products and Relations
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    Chapter 15 On the Structure of Rough Approximations
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    Chapter 16 Modification of Weights of Conflict Profile’s Elements and Dependencies of Attributes in Consensus Model
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    Chapter 17 Reasoning about Information Granules Based on Rough Logic
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    Chapter 18 A Rough Set Framework for Learning in a Directed Acyclic Graph
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    Chapter 19 On Compressible Information Systems
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    Chapter 20 Functional Dependencies in Relational Expressions Based on Or-Sets
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    Chapter 21 On Asymptotic Properties of Rough— Set— Theoretic Approximations. Fractal Dimension, Exact Sets, and Rough Inclusion in Potentially Infinite Information Systems
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    Chapter 22 About Tolerance and Similarity Relations in Information Systems
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    Chapter 23 Rough Sets, Guarded Command Language, and Decision Rules
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    Chapter 24 Collaborative Query Processing in DKS Controlled by Reducts
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    Chapter 25 A New Method for Determining of Extensions and Restrictions of Information Systems
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    Chapter 26 A Logic Programming Framework for Rough Sets
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    Chapter 27 Attribute Core of Decision Table
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    Chapter 28 Signal Analysis Using Rough Integrals
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    Chapter 29 How Much Privacy? — A System to Safe Guard Personal Privacy while Releasing Databases
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    Chapter 30 Rough Clustering: An Alternative to Find Meaningful Clusters by Using the Reducts from a Dataset
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    Chapter 31 Concept Learning with Approximation: Rough Version Spaces
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    Chapter 32 Variable Consistency Monotonic Decision Trees
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    Chapter 33 Importance and Interaction of Conditions in Decision Rules
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    Chapter 34 Time Complexity of Rough Clustering: GAs versus K-Means
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    Chapter 35 Induction of Decision Rules and Classification in the Valued Tolerance Approach
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    Chapter 36 Time Series Model Mining with Similarity-Based Neuro-fuzzy Networks and Genetic Algorithms: A Parallel Implementation
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    Chapter 37 Closeness of Performance Map Information Granules: A Rough Set Approach
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    Chapter 38 Granular Computing on Binary Relations Analysis of Conflict and Chinese Wall Security Policy
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    Chapter 39 Measures of Inclusion and Closeness of Information Granules: A Rough Set Approach
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    Chapter 40 Rough Neurocomputing: A Survey of Basic Models of Neurocomputation
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    Chapter 41 Rough Neurocomputing Based on Hierarchical Classifiers
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    Chapter 42 Using Granular Objects in Multi-source Data Fusion
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    Chapter 43 Induction of Classification Rules by Granular Computing
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    Chapter 44 Acquisition Methods for Contextual Weak Independence
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    Chapter 45 A Method for Detecting Context-Specific Independence in Conditional Probability Tables
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    Chapter 46 Properties of Weak Conditional Independence
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    Chapter 47 A Proposal of Probability of Rough Event Based on Probability of Fuzzy Event
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    Chapter 48 Approximate Bayesian Network Classifiers
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    Chapter 49 Accuracy and Coverage in Rough Set Rule Induction
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    Chapter 50 Statistical Test for Rough Set Approximation Based on Fisher’s Exact Test
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    Chapter 51 Triangulation of Bayesian Networks: A Relational Database Perspective
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    Chapter 52 A New Version of Rough Set Exploration System
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    Chapter 53 Local Attribute Value Grouping for Lazy Rule Induction
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    Chapter 54 Incomplete Data Decomposition for Classification
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    Chapter 55 Extension of Relational Management Systems with Data Mining Capabilities
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    Chapter 56 Reducing Number of Decision Rules by Joining
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    Chapter 57 Scalable Classification Method Based on Rough Sets
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    Chapter 58 Parallel Data Mining Experimentation Using Flexible Configurations
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    Chapter 59 An Optimization of Apriori Algorithm through the Usage of Parallel I/O and Hints
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    Chapter 60 Patterns in Information Maps
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    Chapter 61 Discernibility Matrix Approach to Exception Analysis
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    Chapter 62 Gastric Cancer Data Mining with Ordered Information
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    Chapter 63 A Granular Approach for Analyzing the Degree of Affability of a Web Site
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    Chapter 64 Comparison of Classification Methods for Customer Attrition Analysis
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    Chapter 65 User Profile Model: A View from Artificial Intelligence
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    Chapter 66 Mining the Client’s Life Cycle Behaviour in the Web
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    Chapter 67 PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques
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    Chapter 68 VPRSM Approach to WEB Searching
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    Chapter 69 Rough Set Approach to the Survival Analysis
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    Chapter 70 The Identification of Low-Paying Workplaces: An Analysis Using the Variable Precision Rough Sets Model
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    Chapter 71 A Search for the Best Data Mining Method to Predict Melanoma
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    Chapter 72 Towards the Classification of Musical Works: A Rough Set Approach
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    Chapter 73 Segmentation of Medical Images Based on Approximations in Rough Set Theory
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    Chapter 74 Adaptive Robust Estimation for Filtering Motion Vectors
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    Chapter 75 Rough Set Feature Selection and Diagnostic Rule Generation for Industrial Applications
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    Chapter 76 λ-Connected Approximations for Rough Sets
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    Chapter 77 Adaptive Classifier Construction: An Approach to Handwritten Digit Recognition
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    Chapter 78 The Application of Support Diagnose in Mitochondrial Encephalomyopathies
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    Chapter 79 Obstacle Classification by a Line-Crawling Robot: A Rough Neurocomputing Approach
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    Chapter 80 Rough Neural Network for Software Change Prediction
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    Chapter 81 Handling Spatial Uncertainty in Binary Images: A Rough Set Based Approach
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    Chapter 82 Evolutionary Algorithms and Rough Sets-Based Hybrid Approach to Classificatory Decomposition of Cortical Evoked Potentials
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    Chapter 83 Rough Mereological Localization and Navigation
Overall attention for this book and its chapters
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Title
Rough Sets and Current Trends in Computing
Published by
Springer, Berlin, Heidelberg, January 2002
DOI 10.1007/3-540-45813-1
ISBNs
978-3-54-044274-5, 978-3-54-045813-5
Editors

James J. Alpigini, James F. Peters, Andrzej Skowron, Ning Zhong