Modeling Decisions for Artificial Intelligence

Name: Modeling Decisions for Artificial Intelligence | 16th International Conference, MDAI 2019, Milan, Italy, September 4-6, 2019, Proceedings
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16th International Conference, MDAI 2019, Milan, Italy, September 4-6, 2019, Proceedings

Vicenç Torra Yasuo Narukawa Gabriella Pasi Marco Viviani(Editor)

Springer (Publisher)

Published on 26. August 2019

XIX, 357 pages

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978-3-030-26773-5 (ISBN)

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Content

Intro
Preface
Organization
Abstracts of Invited Talks
Incomplete Knowledge in Computational Social Choice
As Simple as Possible But Not Simpler in Multiple Criteria Decision Analysis: The Robust Stochastic Level Dependent Choquet Integral Approach
Contents
Aggregation Operators and Decision Making
General Chebyshev Type Inequality for Seminormed Fuzzy Integral
1 Introduction
2 Preliminaries
3 Main Results
4 On Existing Sufficient Conditions
5 Special Cases
5.1 Sugeno Integral on [0,1]
5.2 Shilkret Integral on [0,1]
6 Concluding Remarks
References
Convergence in Measure Theorems of the Choquet Integral Revisited
1 Introduction
2 Preliminaries
3 The Conditional Autocontinuity of Nonadditive Measures
4 The Monotone Convergence in Measure Theorem
5 The Fatou and the Reverse Fatou in Measure Lemmas
6 The Dominated Convergence in Measure Theorem
7 The Dual Measure Forms
8 The Extension to Symmetric and Asymmetric Integrals
9 Concluding Remarks
References
Risk-Sensitive Markov Decision Under Risk Constraints with Coherent Risk Measures
1 Introduction
2 Coherent Risk Measure Derived from Risk Averse Utility
3 Markov Decision Processes with Risk Constraints
4 Feasibility of Risk Constraints and Risk-Sensitive Expected Rewards
5 Dynamic Risk-Sensitive Rewards Under Risk Constraints
6 Numerical Examples
References
Set-Based Extended Functions
1 Introduction
2 Set-Based Extended Functions on a General Universe
3 Set-Based Extended Functions on Lattices
4 Set-Based Extended Aggregation Functions on Chains
5 Concluding Remarks
References
Fuzzy Confirmation Measures (a)symmetry Properties
1 Introduction
2 Bayesian and Fuzzy Confirmation Measures
3 Symmetries
4 Lack of Symmetry and Degree of Asymmetry
5 Conclusions
References
Fake News Detection in Microblogging Through Quantifier-Guided Aggregation
1 Introduction
2 Related Work
3 MCDM and Aggregation Operators
3.1 OWA Operators and Linguistic Quantifiers
4 An OWA-Based Approach for Fake News Detection
4.1 Fake News Event Detection on Twitter
4.2 Quantifier-Guided Aggregation Schemes
5 Evaluation
5.1 Implementation Details
5.2 Summarization of Results and Discussion
6 Conclusions
References
Individual, Coalitional and Structural Influence in Group Decision-Making
1 Introduction
2 Influence Model in Group Decision-Making
2.1 Influence in Social Networks
2.2 Influence of Coalitions of Agents
2.3 Social Choice Functions and Social Influence Functions
3 Graphical and Mathematical Expressions of the Three Levels of Influence
3.1 Level I Influence from Independent Agents
3.2 Level II Influence from Coalitional Agents
3.3 Level III Influence from Structural Agents
4 The Interplay Between the Coalitional Influence and the Structural Influence: A Probability-Based Approach
4.1 Individual Influences
4.2 Structural Influences
4.3 Coalitional Influences
5 Discussion, Conclusion and Future Work
References
Betweenness Spaces: Morphism and Aggregation Functions
1 Introduction
2 Ternary Betweenness and Interval Spaces
3 Betweenness Spaces as Abstract Convex Structures
4 Morphisms and Aggregation Functions
5 Concluding Remarks
References
On Idempotent n-ary Uninorms
1 Introduction
2 A First Characterization
3 An Alternative Characterization
References
On Aggregation of Risk Levels Using T-Conorms
1 Introduction
2 Conditions for Aggregation of Risk Factors in Qualitative Risk Assessment Model
3 Aggregation of Risk Levels with Maximum T-Conorm
4 Aggregation of Risk Levels with Lukasiewicz T-Conorm
5 Aggregation of Risk Levels with Combined T-Conorm
6 Example of Aggregated Risk Score
7 Conclusions
References
Towards an Adaptive Defuzzification: Using Numerical Choquet Integral
1 Introduction
2 Fuzzy Measures and the Choquet Integral
3 Fuzzy Rule Based Systems
4 Defuzzification Based on the Choquet Integral
5 Applying the Approach to Cyber-Physical Systems
5.1 Trajectory Search Scenario
6 Concluding Remarks
References
Uninorms and Nullnorms and their Idempotent Versions on Bounded Posets
1 Introduction
2 Basic Notations and Some Known Facts and Notions
3 Existence of Uninorms and Nullnorms on Bounded Posets
4 Idempotent Uninorms and Nullnorms
5 Conclusions
References
Derivative for Discrete Choquet Integrals
1 Introduction
2 Preliminaries
3 Condition for the Existence of a Derivative
4 Possibility Measures
5 Conclusion
References
Data Science and Data Mining
A Non-Negative Matrix Factorization for Recommender Systems Based on Dynamic Bias
Abstract
1 Introduction
2 Problem Description
3 Related Work
4 Proposed Method
4.1 Basic Model
4.2 Probabilistic Distribution
4.3 Factor Matrices
4.4 Bias Matrices
4.5 Algorithm Description
5 Performance Evaluation
5.1 Datasets
5.2 Evaluation Metrics
5.3 Parameter Settings
5.4 Experimental Results
6 Conclusions
Acknowledgments
References
Forecasting Water Levels of Catalan Reservoirs
1 Introduction
2 State of the Art
3 Data Processing
3.1 Reservoirs
3.2 Data Extraction and Feature Selection
4 Methodology and Results
5 Conclusion and Future Work
References
A Predictive Model for MicroRNA Expressions in Pediatric Multiple Sclerosis Detection
1 Introduction
2 The Workflow
3 Data Preprocessing
3.1 Normalization
3.2 Feature Selection
3.3 Class Balancing
4 Model Construction
5 Model Evaluation
6 Conclusions
References
On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy
1 Introduction
2 Preliminaries
2.1 Conventional Collaborative Filtering Method: GroupLens
2.2 CF Using qFCS
2.3 Possibilistic Clustering for Spherical Data Based on Tsallis Entropy
3 Proposed Method
4 Numerical Experiments
5 Conclusion
References
Programmed Inefficiencies in DSS-Supported Human Decision Making
1 Motivation and Background
2 Programmed Inefficiencies in DataWise
3 The DataWise Use Case
3.1 Patient and Model Selection
3.2 Prognostic Support
3.3 Interpretation Support
4 Conclusion
References
Multilayer Identification: Combining N-Grams, TF-IDF and Monge-Elkan in Massive Real Time Processing
Abstract
1 Introduction
2 Multilayer Identification
2.1 The Nucleus of the System
2.2 Upgrading the System. TF-IDF
3 A Variation of Monge-Elkan Algorithm
4 Fine Tuning and Results
4.1 Final Solution
4.2 Fine Tuning
5 Conclusions and Future Work
Acknowledgements
References
An Evidential Clustering for Collaborative Filtering Based on Users' Preferences
1 Introduction
2 Background Related to Evidence Theory
2.1 Basic Concepts and Notations
2.2 Evidential C-Means (ECM)
2.3 Evidential K-Nearest Neighbors
3 Related Works on Collaborative Filtering
4 EC-UBCF: Evidential Clustering User-Based for CF
4.1 Evidential Users' Clustering
4.2 Identifying Clusters
4.3 Users' Neighborhood Selection
4.4 Modeling Users' Neighborhood Ratings
4.5 Generating Users' Neighborhood Predictions
5 Experiments and Discussions
5.1 Evaluation Metrics
5.2 Results
5.3 Scalability Performance
6 Conclusion
References
Analysing the Impact of Rationality on the Italian Electricity Market
1 Introduction and Related Work
2 Some Background: A Brief Description of the Used Methods
3 The Italian Electricity Market
3.1 The Market Configuration
3.2 Market Exchanges
4 Relaxing the Zonal Constraint
4.1 Model Description
4.2 The Optimization Process
4.3 Evaluation of the Proposed Approach
5 Conclusion
References
Analysis of Abstention in the Elections to the Catalan Parliament by Means of Decision Trees
1 Introduction
2 Decision Trees
3 The Data Base
4 Experiments
5 Conclusions and Future Work
References
Making Decisions with Knowledge Base Repairs
1 Introduction
2 Preliminaries
3 Iterative Contractions
4 Choosing the Right Repair
5 Conclusions
References
k-Medoids Clustering Based on Kernel Density Estimation and Jensen-Shannon Divergence
1 Introduction
2 Preliminaries
2.1 k-medoids
2.2 Kernel Density Estimation
2.3 Jensen-Shannon Divergence
3 Proposed Method
4 Experiments
4.1 Experimental Setup
4.2 Experimental Results
4.3 Discussions
5 Conclusions
References
Biases Affecting Human Decision Making in AI-Supported Second Opinion Settings
1 Introduction
2 Methods
3 Results and Analyses
3.1 Plausibility Analysis
3.2 Confirmation Trends Analysis
3.3 Impact on Accuracy Analysis
3.4 Conformity Bias Analysis
4 Discussion and Conclusion
References
Applications of Different CNN Architectures for Palm Vein Identification
1 Introduction
2 The Database
3 Transfer Learning
4 The Proposed Approach
5 Results and Experiments
6 Conclusion and Future Work
References
An Infinite Replicated Softmax Model for Topic Modeling
1 Introduction
2 Preliminaries
2.1 RBM
2.2 RSM
2.3 iRBM
3 Related Work
4 Proposed Model
5 Hybrid Training
6 Experiment Design
7 Results
8 Discussion
9 Conclusion
References
Estimating Optimal Values for Intentional-Value-Substitution Learning
1 Introduction
2 Intentional-Value-Substitution (IVS) Learning
2.1 Method
2.2 Analysis on the Optimal Values with the Target Function
3 Estimation of Optimal Substitution Values Without the Target Function
4 Computational Experiments
4.1 Experimental Setup
4.2 Estimated Values
4.3 Generalization Performance
5 Conclusions
References
Data Privacy and Security
Efficient Near-Optimal Variable-Size Microaggregation
1 Introduction
2 Background
2.1 Microaggregation
2.2 MDAV
2.3 VMDAV
2.4 Clustering and Lloyd's Algorithm
3 Limitations of MDAV and VMDAV
4 ONA: Near-Optimal MicroAggregation
5 Experimental Evaluation
5.1 Evaluated Methods
5.2 Data Sets
5.3 Evaluation Results
6 Conclusions and Future Research
References
Mitigating the Curse of Dimensionality in Data Anonymization
1 Introduction
2 Background
2.1 Principal Component Analysis
2.2 Differentially Private Data Sets
3 PCA-Based Dimensionality Reduction
4 Example: Differential Privacy Anonymization on PCA-Reduced Dimensionality Data
5 Empirical Work
6 Conclusions and Future Research
References
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Modeling Decisions for Artificial Intelligence

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