Note: Intro -- Preface -- Organization -- Abstracts of Invited Talks -- Consistency of Fuzzy Preference Relations -- Towards Distorted Statistics Based on Choquet Calculus -- Assessing the Risk of Default Propagation in Interconnected Sectorial Financial Networks -- Decision Making Tools with Semantic Data to Improve Tourists' Experiences -- Improving Spatial Reasoning in Intelligent Systems: Challenges -- Contents -- Invited Paper -- Graded Logic Aggregation -- Abstract -- 1 A Soft Computing Generalization of Boolean Logic -- 2 Graded Logic Conjecture and Graded Conjunction/Disjunction -- 3 Partitioning of Unit Hypercube -- 4 Conclusions -- References -- Aggregation Operators, Fuzzy Measures and Integrals -- Coherent Risk Measures Derived from Utility Functions -- 1 Introduction -- 2 Value-at-Risks and Coherent Risk Measures -- 3 Weighted Average Value-at-risks with Risk Spectra -- 4 An Optimal Risk Spectrum Derived from Risk Averse Utility Functions -- 5 Examples -- References -- On k-additive Aggregation Functions -- 1 Introduction -- 2 k-maxitive and k-additive Aggregation Functions -- 3 Pseudo-additions -- 4 K-additive Aggregation Functions -- 4.1 Archimedean Pseudo-additions -- 4.2 Archimedean t-conorm-based Pseudo-additions -- 5 Concluding Remarks -- References -- Constructing an Outranking Relation with Weighted OWA for Multi-criteria Decision Analysis -- Abstract -- 1 Introduction -- 2 Weighted OWA Operators -- 2.1 OWAWA -- 2.2 WOWA -- 2.3 IOWA -- 3 Outranking Relations in the ELECTRE Methodology -- 4 Using Weighted OWA in the Overall Concordance Calculation -- 5 Experiments -- 5.1 Finding a Hotel -- 5.2 Generating a Ranking of Universities -- 6 Conclusions and Future Work -- Acknowledgements -- References -- Sugeno Integrals and the Commutation Problem -- 1 Introduction -- 2 A Refresher on 1D Sugeno Integral. , 3 The Commutation of Sugeno Integrals -- 4 Commuting Capacities -- 5 Conclusion -- References -- Characterization of k-Choquet Integrals -- 1 Introduction -- 2 Preliminaries -- 3 Characterization of k-Choquet Integrals -- 3.1 k-Choquet Integrals -- 3.2 The Class Chk,1 -- 3.3 The Class Ch2,2 -- 3.4 The Class Ch2,n -- 3.5 The Class Chk,n -- 4 Conclusion -- References -- Event-Based Transformations of Set Functions and the Consensus Requirement -- 1 Introduction -- 2 Preliminaries -- 3 Linear Operators and Consensus Requirement -- 4 Linear Operators and Event-Based Transformations -- 5 Conclusion -- References -- Association Analysis on Interval-Valued Fuzzy Sets -- 1 Introduction -- 2 Operations on Interval-Valued Fuzzy Sets -- 2.1 Basic Logical Operations -- 3 Introduction to Association Rules -- 4 Association Rules on Interval-Valued Fuzzy Sets -- 4.1 Motivational Example -- 4.2 Computing Support and Confidence on Interval-Valued Data -- 5 Conclusion and Future Work -- References -- Fuzzy Hit-or-Miss Transform Using Uninorms -- 1 Introduction -- 2 Preliminaries -- 3 From Binary to Fuzzy Hit-or-Miss Transform -- 4 Fuzzy Hit or Miss Transform Using Uninorms: Definition and Results -- 5 Experimental Results -- 6 Conclusions and Future Work -- References -- Learning Fuzzy Measures for Aggregation in Fuzzy Rule-Based Models -- 1 Introduction -- 2 Preliminaries -- 3 Methodology -- 3.1 Fuzzy Rule-Based Models Construction -- 3.2 Fuzzy Measure Based on the Rule Confidence -- 3.3 Classification Using the Fuzzy Rules -- 4 Experimental Results -- 4.1 The Diabetic Retinopathy Problem and Dataset -- 4.2 Tests, Results and Discussion -- 5 Conclusion and Future Work -- References -- Decision Making -- Extraction of Patterns to Support Dairy Culling Management -- 1 Introduction -- 2 The JADE Method -- 3 The Anti-unification Concept -- 4 The Data Base. , 5 Modelling the Culling Task -- 6 Experiments -- 6.1 The Model -- 6.2 The Class Production/DIM = VL -- 7 Conclusions -- References -- An Axiomatisation of the Banzhaf Value and Interaction Index for Multichoice Games -- 1 Introduction -- 2 Preliminary Definitions -- 3 Banzhaf Value and Interaction Indices -- 4 Axiomatisation of the Banzhaf Value for Multichoice Games -- 5 Axiomatisation of the Banzhaf Interaction Index -- References -- Fuzzy Positive Primitive Formulas -- 1 Introduction -- 2 Preliminaries -- 3 Fuzzy Positive-Primitive Formulas -- 4 Fuzzy Positive-Primitive Sets of Axioms -- 5 Discussion and Future Work -- References -- Basic Level Concepts as a Means to Better Interpretability of Boolean Matrix Factors and Their Application to Clustering -- 1 Introduction -- 2 Basic Notions -- 2.1 Formal Concept Analysis -- 2.2 Basic Level of Concepts -- 2.3 Boolean Matrix Decomposition -- 3 Boolean Matrix Decomposition: Algorithms -- 3.1 Design of New Algorithms and Experimental Evaluation -- 3.2 Algorithms Utilizing Coverage or Basic Level only -- 3.3 Combining Coverage and Basic Level -- 4 Clustering Algorithm -- 4.1 Algorithm Evaluation -- 5 Conclusion, Related Works, and Future Research -- References -- Fuzzy Type Powerset Operators and F-Transforms -- 1 Introduction -- 2 Preliminary Notions -- 3 L-Fuzzy Type Powerset Theories -- 4 Examples -- 5 Conclusions -- References -- Implicative Weights as Importance Quantifiers in Evaluation Criteria -- Abstract -- 1 Introduction -- 2 Implicative Weights in Conjunctive Aggregators -- 3 Implicative Weight Functions -- 4 GCD and Monotonicity with Respect to Andness and Orness -- 5 Andness-Domination Versus Weight-Domination -- 6 Experimental Comparison of Implicative Weight Models -- 7 Conclusions -- References -- Balancing Assembly Lines and Matching Demand Through Worker Reallocations -- 1 Introduction. , 2 Mathematical Formulation -- 2.1 Input Description -- 2.2 Incorporating Learning and Forgetting Effects -- 2.3 Objective Functions -- 2.4 Restrictions -- 3 Numerical Experiments -- 3.1 Experimental Design -- 3.2 Results -- 3.3 Further Discussion -- 4 Conclusions -- References -- Clustering and Classification -- Optimal Clustering with Twofold Memberships -- 1 Introduction -- 2 K-Means and Rough K-Means -- 3 Algorithms with Twofold Memberships -- 3.1 Second Method with Core Regions of Circles -- 3.2 Categorical Data -- 4 Examples -- 4.1 Illustrative Examples -- 4.2 Real Data -- 5 Conclusion -- References -- Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data -- 1 Introduction -- 2 FCM Clustering and FCM-Type Fuzzy Co-clustering -- 2.1 Fuzzy c-Means (FCM) -- 2.2 Fuzzy Clustering for Categorical Multivariate Data (FCCM) -- 2.3 Three-Mode Fuzzy Clustering for Categorical Multivariate Data (3-Mode FCCM) -- 3 Extension of 3-Mode FCCM for Collaborative 3-Mode FCCM -- 4 Experimental Result -- 5 Conclusion -- References -- Generalized Fuzzy c-Means Clustering and Its Theoretical Properties -- 1 Introduction -- 2 Preliminaries -- 3 Generalized FCM -- 3.1 Optimization Problem -- 3.2 Algorithm, FCF, and Its Property -- 4 Numerical Examples -- 5 Conclusion -- References -- A Self-tuning Possibilistic c-Means Clustering Algorithm -- 1 Introduction -- 2 Background -- 3 Methods -- 4 Results and Discussion -- 4.1 Evaluation Criteria -- 4.2 Tests with Two Clusters in Various Scenarios -- 4.3 Tests with the IRIS Data Set -- 5 Conclusions -- References -- k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values -- 1 Introduction -- 2 Related Work -- 2.1 Partitional Clustering for Categorical Data -- 2.2 Imputation Methods for Categorical Data with Missing Values -- 3 Preliminaries and Problem Statement. , 4 The Proposed k-CCM Algorithm -- 5 Comparative Experiment -- 6 Summary and Future Work -- References -- Data Privacy and Security -- WEDL-NIDS: Improving Network Intrusion Detection Using Word Embedding-Based Deep Learning Method -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Dimension Reduction -- 3.3 Deep Learning Architecture -- 4 Experiment Results and Discussion -- 4.1 Experimental Methodology -- 4.2 Dataset -- 4.3 Multi-classification Using WEDL-NIDS -- 4.4 Comparison with Other Methods -- 5 Conclusions and Future Work -- References -- Anonymization of Unstructured Data via Named-Entity Recognition -- 1 Introduction -- 2 Background -- 2.1 Named-Entity Recognition -- 2.2 Conditional Random Fields -- 3 Related Work -- 4 Methodology -- 4.1 General Approach -- 4.2 Proof of Concept -- 5 Experimental Results -- 5.1 Data Set -- 5.2 Evaluation Metrics -- 5.3 Results and Discussion -- 6 Conclusions and Future Work -- References -- On the Application of SDC Stream Methods to Card Payments Analytics -- 1 Introduction -- 2 Preliminaries -- 2.1 Statistical Disclosure Control -- 2.2 Differential Privacy -- 3 Adapting SDC Methods to the Streaming Setting -- 3.1 Noise Addition -- 3.2 Microaggregation -- 3.3 Rank Swapping -- 3.4 Differential Privacy -- 4 Experiments -- 4.1 Data Description -- 4.2 Metrics for IL and DR -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion -- References -- Correction to: Modeling Decisions for Artificial Intelligence -- Correction to: V. Torra et al. (Eds.): Modeling Decisions for Artificial Intelligence, LNAI 11144, https://doi.org/10.1007/978-3-030-00202-2 -- Author Index.