Modeling Decisions for Artificial Intelligence, 1st ed. 2018 15th International Conference, MDAI 2018, Mallorca, Spain, October 15-18, 2018, Proceedings Lecture Notes in Artificial Intelligence Series

This book constitutes the proceedings of the 15th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2018, held in Mallorca, Spain, in October 2018.

The 24 papers presented in this volume were carefully reviewed and selected from 43 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: aggregation operators, fuzzy measures and integrals; decision making; clustering and classification; and data privacy and security.

Invited Paper.- Graded logic aggregation.- Aggregation Operators, Fuzzy Measures and Integrals.- Coherent Risk Measures Derived from Utility Functions.- On k-+-additive Aggregation Functions.- Constructing an outranking relation with weighted OWA for multi-criteria decision analysis.- Sugeno integrals and the commutation problem.- Event-based Transformations of Set Functions and The Consensus Requirement.- Association Analysis on Interval-valued Fuzzy Sets.- Fuzzy Hit-or-Miss Transform Using Uninorms.- Learning fuzzy measures for aggregation in fuzzy rule-based models.- Decision making.- Extraction of Patterns to support Dairy Culling Management.- An axiomatisation of the Banzhaf value and interaction index for multichoice games.- Fuzzy Positive Primitive Formulas.- Basic Level Concepts as a Means to Better Interpretability of Boolean Matrix Factors and their Application to Clustering.- Fuzzy type powerset operators and F-transforms.- Implicative weights as Importance Quantifiers in Evaluation Criteria.- Balancing Assembly Lines and Matching Demand through Worker Reallocations.- Clustering and Classification.- Optimal Clustering with Twofold Memberships.- Privacy Preserving Collaborative Fuzzy Co-clustering of Three-mode Cooccurrence Data.- Generalized Fuzzy c-Means Clustering and Its Theoretical Properties.- A self-tuning possibilistic c-means clustering algorithm.- k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values.- Data privacy and security.- WEDL-NIDS:Improving Network Intrusion Detection using Word Embedding-based Deep Learning Method.- Anonymization of Unstructured Data Via Named-Entity Recognition.- On the Application of SDC Stream Methods to Card Payments Analytics.