Rough Sets

Name: Rough Sets | International Joint Conference, IJCRS 2017, Olsztyn, Poland, July 3-7, 2017, Proceedings, Part I
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International Joint Conference, IJCRS 2017, Olsztyn, Poland, July 3-7, 2017, Proceedings, Part I

Lech Polkowski Yiyu Yao Piotr Artiemjew Davide Ciucci Dun Liu Dominik Slezak Beata Zielosko(Editor)

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Published on 22. June 2017

L, 693 pages

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978-3-319-60837-2 (ISBN)

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Content

Intro
Preface
Organization
Invited Talks
Structure and Interpretation of Classifiers - The Rule Networks
Realizing Applied, Useful Self-organizing Cyber-physical Systems with the HARMS Integration Model
Granular Data Mining and Uncertainty Modeling: Concepts, Features and Applications
A Framework for Exploring Disciplines of Science: Dynamic Processes Within a Static Depository of Knowledge
Big Data Analysis by Rough Sets and Granular Computing
Exploratory Knowledge Discovery and Approximations: An FCA Perspective
More with Less - A New Paradigm in Modern Machine Learning
A Tutorial on Mereotopology: Contact Structures, Crisp and Rough
Rough Sets for Big Data - A Tutorial on Applications in Life Sciences
Mereotopology: Static and Dynamic
Revisiting Indiscernibility as the foundation of Rough Sets
Contents -- Part I
Contents -- Part II
Invited Talks
Zdzislaw Pawlak: Man, Creator and Innovator of Computer Sciences
Data-Driven Granular Cognitive Computing
1 Introduction
2 Cognitive Computing
3 Granular Computing
4 Data-driven Granular Cognitive Computing
5 Hierarchical Structuralism: A New Mechanism for Artificial Intelligence
6 Conclusion
References
Advances in Rough Set Based Hybrid Approaches for Medical Image Analysis
1 Introduction
2 Image Analysis Using Rough Sets
3 Recent Advances of Rough Sets in Medical Imaging
3.1 Skull Stripping for 3-D Brain MR Images
3.2 Bias Field Correction in MR Images
3.3 New Probability Distribution for Tissue Class Modeling
3.4 Segmentation of Brain MR Volumes
3.5 Brain Tumor Detection
3.6 Segmentation of HEp-2 Cell IIF Images
References
User Friendly NPS-Based Recommender System for Driving Business Revenue
1 Introduction
2 Semantic Similarity
3 Hierarchical Agglomerative Method for Improving NPS
4 Action Rules
5 Meta Actions and Triggering Mechanism
6 Text Mining
7 Visualization
8 Future Work
References
The Multi-purpose Role of the Relational Approach to Classic and Generalized Approximation Spaces. A Tutorial
1 Introduction
2 Binary Relations and Their Basic Operations
3 Intensional and Extensional Constructors
4 Duality and Adjointness
5 Relational Constructors and Operators Vs Approximations
6 Further Applications
6.1 Covering-Based Rough Sets
6.2 Approximation of Relations
6.3 Dependency Relations
References
General Rough Sets
Heterogeneous Approximate Reasoning with Graded Truth Values
1 Introduction and Motivations
2 The Family of Logics
3 Relationship to Approximate Reasoning
3.1 Deriving Truth-Degrees from Fuzzy Values
3.2 Deriving Truth-Degrees from Intuitionistic Fuzzy Sets
3.3 Deriving Truth-Degrees from Generalized Fuzzy Sets
3.4 Deriving Truth-Degrees from Rough Sets
3.5 Deriving Truth-Degrees from Graded Rough Sets
4 The Family of Rule Languages
4.1 The Basic Rule Language
4.2 Introspection Operators
4.3 Integrating Approximate Reasoning with Rules
5 Case Studies
5.1 From Approximate Reasoning to the Rule Language: An Image Recognition Scenario
5.2 Integration of Heterogeneous Approximate Reasoning Techniques: A Chemical Warehouse Monitoring System
6 Conclusions
References
Computer Certification of Generalized Rough Sets Based on Relations
1 Introduction
2 Generalized Rough Sets
2.1 Listed Characteristic Formulas
2.2 Hidden vs. Visible Arguments
2.3 Refactoring of the Existing Proof
3 Relational vs. Structural View for Rough Sets
4 The Gap
5 Attributes
6 Automatizing Properties
7 Some Statistics
8 Conclusions and Further Work
References
New Algebras and Logic from a Category of Rough Sets
1 Introduction
2 Categories of Rough Sets
3 Algebras of Strong Subobjects in RSC and RSC(C)
4 Intuitionistic Logic with Minimal Negation
5 Conclusions
References
Rough and Near: Modal History of Two Theories
1 Introduction
2 Rough Sets: Modal Story
3 Spatially and Descriptively Near Sets
4 Modal Rendering of Nearness
5 Conclusions
References
Multi-stage Optimization of Matchings in Trees with Application to Kidney Exchange
1 Introduction
2 Graph D(G) Corresponding to Tree G
3 Multi-stage Optimization of Matchings
4 Example
5 Conclusions
References
A Rough-Set Based Solution of the Total Domination Problem
1 Introduction
2 Preliminaries
2.1 Attribute Reduction in Rough Set Theory
2.2 The Domination Problem in Graph Theory
3 An Induced Decision Table of Graph
4 Algorithms for the Domination Problem Based on Rough Set
5 Experiments
6 Conclusions
References
Yet Another Kind of Rough Sets Induced by Coverings
1 Introduction and Motivation
2 Rough Sets and Approximations
3 Coverings, Components and Definability
4 Rough Sets Induced by Coverings
5 Final Comments
References
Approximation Operators in Covering Based Rough Sets from Submodular Functions
1 Introduction
2 Preliminaries
2.1 Pawlak's Rough Set Approximations
2.2 Covering Based Rough Sets
3 SubModular Functions
3.1 Closures
3.2 Submodular Functions from Coverings
3.3 Neighborhood Operators
4 List of New Approximation Operators
5 Conclusions
References
Toward Adaptive Rough Sets
1 Introduction
2 Rudiments of Rough Sets and Complex Granules
2.1 Rough Sets
2.2 Complex Granules
3 Towards Adaptive Decision Strategies: Focusing on Different Perspectives of Agents with Time
4 Adaptive Information System: An Outline
4.1 Formal Counterpart
5 Concluding Remarks
References
Optimal Scale Selections in Consistent Generalized Multi-scale Decision Tables
1 Introduction
2 Information Systems and Belief Functions
2.1 Information Systems and Decision Tables
2.2 Belief Structures and Belief Functions
3 Knowledge Representations in Generalized Multi-scale Information Tables
3.1 Multi-scale Information Tables
3.2 Scale Combinations in Generalized Multi-scale Information Tables
3.3 Information Granules and Rough Approximations in Multi-scale Information Tables
4 Optimal Scale Selections in Consistent Generalized Multi-scale Decision Tables
5 Conclusion
References
A Framework for Analysis of Granular Neural Networks
1 Introduction
2 GNN Axioms
3 GNN as a Robust Tool for Information Aggregation
3.1 Overall Framework
3.2 A Schematic Example
4 Discussion
5 Summary
References
Petri Nets over Ontological Graphs: Conception and Application for Modelling Tasks of Robots
1 Introduction
2 Petri Nets over Ontological Graphs
3 Conclusions
References
Fractal Analysis Approaches to Granular Computing
1 Introduction
2 Fractal Analysis and Concepts
3 Connection in Granular Computing and Fractal Analysis
3.1 Granules and Fractals
3.2 Relationships
3.3 Granulation and Fractal Dimension
4 Fractal Analysis Application and Its Granular Computing Structure
5 Conclusion
References
Generating Natural Language Explanations from Knowledge-Based Systems Results, Using Ontology and Discourses Patterns
Abstract
1 Introduction
2 Bioleaching Process and Work Context
2.1 Work Context
2.2 Domain Specifications
2.3 Knowledge-Based Systems
2.4 Ontology
3 Software Methodology
4 Proposed Method for Generating Natural Language Explanations
4.1 The Domain Knowledge
4.2 Interest Knowledge
4.3 Discourse Patterns
4.4 Abstraction
4.5 Planning
5 Validation
5.1 Examples
5.2 Practical Utility
6 Conclusions and Future Work
Acknowledgements
References
Discernibility Matrix and Rules Acquisition Based Chinese Question Answering System
1 Introduction
2 Related Works
3 Rules Acquisition and Attribute Vectorization
3.1 Rules Acquisition of Chinese QA Sentences
3.2 Vector Representation of Attribute Word
4 Method of Matching QA Patterns
5 Experiment
6 Conclusion
References
Methods Based on Pawlak's Model of Conflict Analysis - Medical Applications
1 Introduction
2 An Overview of Pawlak's Conflict Model and Proposed Modifications
3 Experiments
4 Conclusions
References
Comprehensive Operational Control of the Natural and Anthropogenic Territory Safety Based on Analytical Indicators
Abstract
1 Introduction
2 Comprehensive Monitoring of the Territory Safety
3 Analytical Modelling of the State of Technosphere and Environment Objects
4 Operational Assessment of the Territory Safety Based on Analytical Indicators
5 Implementation of Operational Control Tools
6 Conclusion
References
Metaphor Detection Using Fuzzy Rough Sets
1 Introduction
2 Related Work
3 A Model for Metaphor Detection Using Fuzzy Rough Sets
3.1 Problem Representation
3.2 Feature Selection
3.3 Rule Induction
4 Experiments and Results
4.1 Discussion
5 Conclusion
References
Acr2Vec: Learning Acronym Representations in Twitter
1 Introduction
2 Related Work
2.1 Word Embeddings
2.2 Acronym Embeddings
2.3 Polarity Classification
3 Twitter Acronym Dataset
3.1 Resources and Tools
3.2 Data Integration
3.3 Data Correction
4 Acr2Vec Framework with Three Acronym Embedding Models
4.1 Max Pooling Definition Embedding Model (MPDE)
4.2 Average Pooling Definition Embedding Model (APDE)
4.3 Paragraph-Like Acronym Embedding Model (PLAE)
5 Experimental Results
5.1 Datasets
5.2 Qualitative Performance on Acr2Vec
5.3 Quantitative Performance on Acr2Vec
6 Conclusions
References
Attribute Reduction on Distributed Incomplete Decision Information System
1 Introduction
2 Preliminaries
3 Rough Set in Distributed Incomplete Decision Information System
4 Attribute Reduction on Distributed Incomplete Decision Information System
5 Experimental Studies
5.1 The Experiment Result of Group 1
5.2 The Experiment Result of Group 2
6 Conclusions
References
The Attribute Reductions Based on Indiscernibility and Discernibility Relations
1 Introduction
2 Indiscernibility and Discernibility Relations
3 The Reduction Based on -Relative Relations
4 The Reduction Based on -Relative Relations
5 Concluding Remarks
References
Stable Rules Evaluation for a Rough-Set-Based Bipolar Model: A Preliminary Study for Credit Loan Evaluation
Abstract
1 Introduction
2 Preliminary
2.1 Non-deterministic Information Systems (NISs)
2.2 Stability Factor for Measuring DRSA Decision Rules
3 Bipolar Decision Model Enhanced with Stable Possible Rules
4 A Brief Illustration Example of Personal Credit Loan Evaluation
4.1 Initial Bipolar Model with Deterministic Values
4.2 Evaluating Stability Factor of Decision Rules
5 Concluding Remarks
Acknowledgment
References
On Combining Discretisation Parameters and Attribute Ranking for Selection of Decision Rules
1 Introduction
2 Background Information
2.1 Supervised Discretisation
2.2 Ranking of Attributes
2.3 Selection of Rules
2.4 Rough Set Approaches
2.5 Stylometric Analysis of Texts
3 Research Framework
3.1 Input Datasets
3.2 Discretisation Parameters
3.3 Ranking with Relief
3.4 Defined Rule Quality Measures
3.5 DRSA Rules
3.6 CRSA Rules
4 Performed Experiments
4.1 Selection of Rules by Their Condition Attributes
4.2 Selection of Rules by Quality Measures
4.3 Summary of Test Results
5 Conclusions
References
Induction of Rule for Differential Diagnosis
1 Introduction
2 Probabilistic Rules
3 Characterization Sets
3.1 Characterization Sets
4 Rule Induction
4.1 Rule Induction Process
4.2 Similarity
5 Example
5.1 Grouping
5.2 Data Decomposition
5.3 Rule Induction
6 Experimental Results
7 Conclusion
References
Attribute Reduction: An Ensemble Strategy
1 Introduction
2 Preliminary Knowledge
2.1 Variable Precision Rough Sets
2.2 Variable Precision Fuzzy Rough Sets
3 Attribute Reduction
3.1 Heuristic Algorithm
3.2 Ensemble Heuristic Algorithm
4 Experiments
4.1 Data Sets
4.2 Configuration
4.3 Experimental Results and Discussions
5 Conclusions
References
On Importance of Rows for Decision Tables
1 Introduction
2 Main Notions and Tools
2.1 Decision Tables, Tests and Reducts
2.2 Characteristic Functions
2.3 Canonical Forms of Decision Tables
2.4 Importance of Rows
3 Experimental Results
4 Conclusions
References
Assignment Reduction of Relation Decision Systems
1 Introduction
2 Preliminaries
3 An Assignment Reduction Algorithm for Relation Decision Systems
4 An Application to Decision Tables
5 An Application to Ordered Information Systems
6 Conclusions
References
Automatically Determining the Popularity of a Song
Abstract
1 Introduction
2 Similar Applications
3 Data Acquisition
3.1 Lyrics Retrieval
3.2 Extraction of the Main Frequencies from the Songs' Melody
3.3 Extracting the Number of Views and Number of "Like" Votes on the YouTube Platform
4 Used Algorithms
4.1 Logistic Regression
4.2 Support Vector Machines (SVM)
4.3 K-Nearest Neighbors (KNN)
5 Obtained Results
5.1 Predicting the Number of Views
5.2 Predicting the Number of "Like" Votes
6 Conclusions and Further Development
Acknowledgments
References
iPDO: An Effective Feature Depth Estimation Method for 3D Face Reconstruction
1 Introduction
2 Face Surface Reconstruction
2.1 A Generic Framework of Depth Estimation from Two Images
2.2 Basic Idea of iPDO
2.3 Depth Fusion and Dense 3D Face Modeling
3 Experiments and Analysis
3.1 Experiment Configuration
3.2 Experimental Results
4 Conclusions
References
Proposal of Dominance-Based Rough Set Approach by STRIM and Its Applied Example
1 Introduction
2 Conventional Rough Sets and DRSA
3 Conventional STRIM
4 Example of STRIM Applying to a Real-World Dataset
5 Studies from an Ordinal Scale and Proposal of DOMSTRIM
6 Proposal of Consistency Index for Dominance
7 Examinations by DOMLEM
8 Conclusions
References
Regularization and Shrinkage in Rough Set Based Canonical Correlation Analysis
1 Introduction
2 Basics of Canonical Correlation Analysis, Rough Sets and Rough Hypercuboid Approach
2.1 Canonical Correlation Analysis
2.2 Rough Sets
2.3 Rough Hypercuboid Approach
3 Proposed Method
4 Experimental Results and Discussion
5 Conclusion and Future Directions
References
Temporal Relations of Rough Anti-patterns in Software Development
1 Introduction
1.1 Remainder of This Paper
1.2 Contributions of This Paper
2 Software Development
2.1 Software Structure
2.2 Software Metrics
2.3 Software Snapshot
2.4 Software Evolution
2.5 Design Patterns and Anti-patterns
3 Finding Anti-patterns
3.1 Raw Data Fetching
3.2 Software Pattern Matching
3.3 Pattern Instance
3.4 Overlapping and Distance Between Patterns
3.5 Closeness of Pattern Instances
3.6 Pattern Instance Lifespan
3.7 Temporal Pattern Relations
3.8 Classification of Temporal Pattern Relations
4 Experimental Validation
4.1 Definition of Anti-patterns
4.2 Occurrences and Co-occurrences of Patterns
4.3 Results
5 Related Work
6 Conclusions and Future Work
6.1 Spatio-Temporal Patterns in Software Development
6.2 Rough Software Patterns
6.3 Future Work
References
Temporal Prediction Model for Social Information Propagation
1 Introduction
2 Related Work
3 Scaling Clustering Based Temporal Prediction Model
4 Experiments
4.1 Clustering Analysis
4.2 SCTPM Experiments
4.3 Analysis of PB and PV
5 Conclusion
References
Characteristic Sets and Generalized Maximal Consistent Blocks in Mining Incomplete Data
1 Introduction
2 Incomplete Data Sets
3 Characteristic Sets and Maximal Consistent Blocks
4 Probabilistic Approximations
4.1 Probabilistic Approximations Based on Characteristic Sets
4.2 Probabilistic Approximations Based on Maximal Consistent Blocks
5 Definability
6 Experiments
7 Conclusions
References
Rough Sets in Incomplete Information Systems with Order Relations Under Lipski's Approach
1 Introduction
2 Rough Sets by Classes from Order Relations in Complete Ordered Information Systems
3 Rough Sets Based on Possible World Semantics in Incomplete Ordered Information Systems
4 Conclusion and Future Work
References
A Measure of Inconsistency for Simple Decision Systems over Ontological Graphs
1 Introduction
2 Theoretical Background
2.1 Binary Relations, Basic Knowledge Granules and Rough Sets
2.2 Decision Systems over Ontological Graphs
2.3 Fuzzy Sets
3 Assessment of Basic Knowledge Granules
4 Conclusions
References
A Rough View on Incomplete Information in Games
1 Introduction
2 Missing Information in Games
2.1 Introductional and Notational Remarks
2.2 Imperfect and Incomplete Information
3 Relationship of Incomplete Information in Games and Rough Sets
3.1 Transforming a Game with Incomplete Information into a Rough Decision Table
4 Roughness of Games
4.1 Rough Analyses of the Game with Imperfect Information
4.2 Roughness with Respect to Incomplete Information
5 Conclusion
References
A Proposal of Machine Learning by Rule Generation from Tables with Non-deterministic Information and Its Prototype System
1 Introduction
2 Background of Rules in NISs and NIS-Apriori Based Rule Generation
2.1 RNIA and Rule Generation
2.2 NIS-Apriori Algorithm and Its Implementation
3 Machine Learning by Rule Generation in NISs
3.1 Motivation and Purpose
3.2 Some Properties on CR(i) and PR(i)
3.3 The Framework of MLRG and Two Strategies
4 An Example of MLRG
5 SQL Procedures in MLRG
5.1 NRDF Format
5.2 SQL Procedure step1
5.3 SQL Procedure pstep
5.4 SQL Procedure apri
5.5 Implementation of MLRG Procedures in SQL
6 Concluding Remarks and Discussion
References
Rough Set Analysis of Classification Data with Missing Values
1 Introduction
2 Basics of IRSA and DRSA
2.1 Basics of IRSA
2.2 Basics of DRSA
3 Different Ways of Handling Missing Values in IRSA and DRSA
3.1 Adaptations of IRSA to Handle Missing Values
3.2 Desirable Properties of IRSA Adapted to Handle Missing Values
3.3 Adaptations of DRSA to Handle Missing Values
3.4 Desirable Properties of DRSA Adapted to Handle Missing Values
4 Conclusions
References
The Optimal Estimation of Fuzziness Parameter in Fuzzy C-Means Algorithm
1 Introduction
2 Methodology
2.1 The FCM Algorithm
2.2 The XB Index
2.3 The Parameter m as a Random Variable
2.4 Simulated Annealing Algorithm
3 The Estimation of m
3.1 Simulation Study
4 The Numerical Experiment
4.1 Concluding Remarks
5 Conclusion
References
Supercluster in Statics and Dynamics: An Approximate Structure Imitating a Rough Set
1 Introduction
2 Dynamic Supercluster Model
2.1 Static Data
2.2 Supercluster at Dynamic Data
3 Building Superclusters
4 Application
4.1 IFCS Network Superclusters
4.2 The Structure of a Novel's Plot
5 Conclusions and Future Work
References
Integration of Gene Expression and Ontology for Clustering Functionally Similar Genes
1 Introduction
2 Proposed Dissimilarity Measure
2.1 Selection of Initial Cluster Prototypes
3 Gene Expression Data Sets Used
4 Results and Discussions
4.1 Optimum Clustering Solutions
4.2 Importance of Integrated Dissimilarity Measure
4.3 Comparative Performance Analysis of Different Clustering Algorithms
4.4 Qualitative Performance Analysis
4.5 Performance of Clustering Algorithms in Terms of Cluster Validity Indices
5 Conclusion
References
Multi-view Clustering Algorithm Based on Variable Weight and MKL
1 Introduction
2 Related Work
3 Multi-view Clustering Algorithm Based on Variable Weight and MKL (MVMKC)
3.1 Kernel Function
3.2 Weighted Gaussian Kernel
3.3 MVMKC Algorithm
3.4 Algorithm Derivation
4 Experiment
4.1 Experiment Setting
4.2 Results
5 Conclusion
References
An Overlapping Clustering Approach with Correlation Weight
1 Introduction
2 Related Work
2.1 Overlapping Clustering
2.2 Partitioning Overlapping Clustering
3 Overlapping Clustering with Correlation Weight
3.1 Motivation
3.2 OCCW Algorithm
4 Experiments
4.1 Datasets and Evaluation Standard
4.2 Experiment Results
5 Conclusions
References
Software and Systems for Rough Sets
A Metadata Diagnostic Framework for a New Approximate Query Engine Working with Granulated Data Summaries
1 Introduction
2 The New Approximate Query Engine
3 Towards the Design of Metadata Repository
3.1 Extracting Metadata from the Engine
3.2 Initial Designs for Metadata Visualization
3.3 Relational Schema for Metadata Contents
4 Working with Metadata Tables
4.1 Data Demographics
4.2 Towards Granular Machine Learning
4.3 Approximating Column Domains
5 Conclusions
References
Scalable Maximal Discernibility Discretization for Big Data
1 Introduction
2 Optimal Discretization of Continuous Attributes
3 Apache Spark Implementation
4 Experimental Results
4.1 Scalability
4.2 Speedup
4.3 Sizeup
5 Conclusions and Future Research
References
Hardware Supported Rule-Based Classification on Big Datasets
1 Introduction
2 Introductory Information
2.1 Algorithm for Hardware Supported Classification
2.2 Hardware Dataset Processing in Proposed Algorithm
2.3 Data to Conduct Experimental Research
3 System Architecture and Hardware Realization
3.1 Softcore Control Unit
3.2 Hardware Implementation
4 Experimental Results
5 Conclusions
References
Introducing NRough Framework
1 Introduction
2 Key Features
2.1 Data Representation
2.2 Approximate Decision Reducts
2.3 Approximate Decision Reduct Classifier Ensembles
2.4 Other Machine Learning Algorithms
2.5 Model Evaluation
3 Architecture
4 License
5 Other Frameworks
6 Conclusions and Future Work
References
Correction to: Toward Adaptive Rough Sets
Correction to: Chapter "Toward Adaptive Rough Sets" in: L. Polkowski et al. (Eds.): Rough Sets, LNAI 10313, https://doi.org/10.1007/978-3-319-60837-2_14
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Rough Sets

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