Graph-based representation and reasoning : 26th International Conference on Conceptual Structures, ICCS 2021, virtual event, September 20-22, 2021 : proceedings

Preface
Organization
Reconciling Knowledge-Based and Data-Driven AI for Human-in-the-Loop Machine Learning (Abstract of Invited Talk)
Abstract of Tutorials
Foundations of Knowledge Graphs
Concepts and Reasoning: Alternative Approaches
Contents
Applications of Conceptual Structures
On the Use of FCA Models in Static Analysis Tools to Detect Common Errors in Programming
	1 Introduction
	2 Theoretical Background
		2.1 FCA
		2.2 Static Code Analysis with Pylint
	3 Related Work
	4 Concept Lattice for the Selected Criterion
	5 Applying FCA to Detect Common Programming Errors
		5.1 Data Collection
		5.2 Common Errors Related to Design
	6 Conclusions and Future Work
	References
Nested Conceptual Graphs for Information Fusion Traceability
	1 Introduction
	2 Context
		2.1 Conceptual Graphs as Formalism for Information Representation
		2.2 InSyTo: A Toolbox for Information Fusion
		2.3 The Need for Traceability in Information Fusion
	3 Tracing Information Fusion with InSyTo
		3.1 General Approach
		3.2 Background: Simple, Nested and Typed Conceptual Graphs
		3.3 Nested Typed Graphs as Concepts' Lineage
		3.4 Information Fusion
		3.5 Tracked Fusion of Situation Graphs
	4 Discussion and Conclusion
	References
Generating Layered Enterprise Architectures with Conceptual Structures
	1 Introduction
	2 The Metamodel Diagram
	3 Activating and Layering the Metamodel
		3.1 Methodology
		3.2 Findings
		3.3 Layered Formal Concept Lattice
	4 Discussion
		4.1 Implications
		4.2 Current Limitations
		4.3 Future Research
	5 Conclusion
	References
An Approach to Identifying the Most Predictive and Discriminant Featuresin Supervised Classification Problems
	1 Introduction
	2 Prediction and Discrimination
	3 Selecting Features
		3.1 Prediction, Discrimination and Feature Importance
		3.2 Identifying Important Features
	4 Experimental Results
	5 Discussion and Conclusion
	References
Combining Implications and Conceptual Analysis to Learn from a Pesticidal Plant Knowledge Base
	1 Introduction
	2 Approach
	3 Three Representations of the Datasets
	4 Evaluation
		4.1 Analysis of the Implications Obtained for the 3 Representations
		4.2 Discussion
	5 Related Work
	6 Conclusion
	References
Ranking Schemas by Focus: A Cognitively-Inspired Approach
	1 Introduction
	2 Defining Focus
	3 Focus Metrics
		3.1 Focuse
		3.2 Focusk
	4 Ranking KBSs
	5 Validating Focus
		5.1 Focuse Validation
		5.2 Focusk Validation
	6 Related Work
	7 Conclusion
	References
Theory on Conceptual Structures
Improving the Performance of Lindig-Style Algorithms with Empty Intersections
	1 Introduction
	2 Preliminaries
	3 Lindig's Algorithm and Its Enhancement
		3.1 Lindig's Algorithm
		3.2 Use of Empty Intersections
		3.3 Computing a Concept Lattice
		3.4 Implementation Aspects
	4 Evaluation
		4.1 Real World Datasets
		4.2 Synthetic Data
	5 Conclusions and Future Research
	References
Quantifying the Conceptual Error in Dimensionality Reduction
	1 Introduction
	2 Scales and Data
		2.1 Scales-Measures
	3 Conceptual Errors in Data Scaling
		3.1 Representation and Structure of Conceptual Scaling Errors
		3.2 Computational Tractability
	4 Experimental Evaluation
		4.1 Qualitative Analysis
	5 Related Work
	6 Conclusion
	References
Conceptual Relevance Index for Identifying Actionable Formal Concepts
	1 Introduction
	2 Background
	3 Conceptual Relevance (CR) Index
	4 Experimental Evaluation
	5 Conclusion
	References
Attribute Selection Using Contranominal Scales
	1 Introduction
	2 Foundations
	3 Related Work
	4 Computing Contranominal Scales
		4.1 Computing Contranominals Is Hard
		4.2 Baseline Algorithms
		4.3 ContraFinder: An Algorithm to Compute Contranominal Scales
		4.4 Speedup Techniques
	5 Attribute Selection
		5.1 Properties of Implications
	6 Evaluation and Discussion
		6.1 Datasets
		6.2 Runtime of ContraFinder
		6.3 Structural Effects of -Adjusting
		6.4 Knowledge in the -Adjusted Context
		6.5 Discussion
	7 Conclusion
	References
Packing Problems, Dimensions and the Tensor Product of Complete Lattices
	1 Introduction
	2 Basics of Formal Concept Analysis
	3 The Inner Order 2-Dimension
	4 The Inner Orthodimension
	5 Breadth, VC-Dimension and Graph Parameters
	6 Dimensions of the Tensor Product of Complete Lattices
	7 Conclusion
	References
Mining Conceptual Structures
Random Generation of a Locally Consistent Spatio-Temporal Graph
	1 Introduction
	2 Preliminaries
		2.1 Graphs Simulation
		2.2 RCC8 Relations
		2.3 Consistency
	3 Generation of Locally Consistent ST Graphs
	4 Experimentations
		4.1 Variation of the Node Number
		4.2 Variation of the Edge Number
		4.3 Variation of the Pattern Number
	5 Conclusion
	References
Mining Contextual Rules to Predict Asbestos in Buildings
	1 Introduction
	2 Related Work
	3 Asbestos Ontology
	4 CRA-Miner Approach
		4.1 Contextual Rules for Asbestos Prediction
		4.2 Evolution of the Presence of Asbestos over Time
		4.3 Algorithm CRA-Miner
	5 Experiments
	6 Conclusion
	References
Temporal Sequence Mining Using FCA and GALACTIC
	1 Introduction
	2 Preliminaries
		2.1 Temporal Sequences
		2.2 The NextPriorityConcept Algorithm
	3 NextPriorityConcept for Temporal Sequences
		3.1 Description for Temporal Sequences
		3.2 Strategies and Selectors for Temporal Sequences
		3.3 Measures
	4 Experiments
		4.1 Comparison of Strategies
		4.2 Constraints
	5 Conclusion
	References
Restricted Bi-pattern Mining
	1 Introduction
	2 Single Pattern and Bi-pattern Mining
		2.1 Core Closed Single Pattern Mining
		2.2 Core Closed Bi-pattern Mining
	3 Restricted Bi-pattern
	4 Conclusion
	References
A Semantic-Based Approach for Assessing the Impact of Cyber-Physical Attacks: A Healthcare Infrastructure Use Case
	1 Introduction
	2 Semantic-Based Impact Propagation Approach
		2.1 Semantic Modeling
		2.2 Impacts Propagation
		2.3 Estimating Impact Score
	3 Experiments and Results
		3.1 Implementation
		3.2 Use Case
		3.3 Evaluation
	4 Related Work
	5 Conclusion
	References
Author Index