| TÃtulo : |
13th International Conference, SUM 2019, Compiègne, France, December 16–18, 2019, Proceedings |
| Tipo de documento: |
documento electrónico |
| Autores: |
Ben Amor, Nahla, ; Quost, Benjamin, ; Theobald, Martin, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2019 |
| Número de páginas: |
XI, 452 p. 220 ilustraciones, 57 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-35514-2 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Inteligencia artificial Ciencias de la Computación Informática Estadistica matematica Lógica informática y fundamentos de la programación Probabilidad y EstadÃstica en Informática |
| Clasificación: |
|
| Resumen: |
Este libro constituye las actas arbitradas de la 13.ª Conferencia Internacional sobre Gestión Escalable de la Incertidumbre, SUM 2019, que se celebró en Compiègne, Francia, en diciembre de 2019. Los 25 artÃculos completos, 4 breves, 4 tutoriales y 2 artÃculos principales invitados presentados en este volumen fueron cuidadosamente revisado y seleccionado entre 44 presentaciones. La conferencia está dedicada a la gestión de grandes cantidades de información compleja, incierta, incompleta o inconsistente. Se han desarrollado nuevos enfoques sobre probabilidades imprecisas, teorÃa de conjuntos difusos, teorÃa de conjuntos aproximados, representaciones de incertidumbre ordinal o incluso modelos puramente cualitativos. |
| Nota de contenido: |
An Experimental Study on the Behaviour of Inconsistency Measures -- Inconsistency Measurement Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study -- The Hidden Elegance of Causal Interaction Models -- Computational Models for Cumulative Prospect Theory: Application to the Knapsack Problem Under Risk -- On a new evidential C-Means algorithm with instance-level constraints -- Hybrid Reasoning on a Bipolar Argumentation Framework -- Active Preference Elicitation by Bayesian Updating on Optimality Polyhedra -- Selecting Relevant Association Rules From Imperfect Data -- Evidential classification of incomplete data via imprecise relabelling: Application to plastic sorting -- An analogical interpolation method for enlarging a training dataset -- Towards a reconciliation between reasoning and learning - A position paper -- CP-nets, π-pref nets, and Pareto dominance -- Measuring Inconsistency through Subformula Forgetting Explaining Hierarchical Multi-Linear Models -- Assertional Removed Sets Merging of DL-Lite Knowledge Bases -- An Interactive Polyhedral Approach for Multi-Objective Combinatorial Optimization with Incomplete Preference Information -- Open-Mindedness of Gradual Argumentation Semantics -- Approximate Querying on Property Graphs -- Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants -- On cautiousness and expressiveness in interval-valued logic -- Preference Elicitation with Uncertainty: Extending Regret Based Methods with Belief Functions -- Evidence Propagation and Consensus Formation in Noisy Environments -- Order-Independent Structure Learning of Multivariate Regression Chain Graphs -- l Comparison of analogy-based methods for predicting preferences -- Using Convolutional Neural Network in Cross-Domain Argumentation Mining Framework -- ConvNet and Dempster-Shafer Theory for Object Recognition -- On learning evidential contextual corrections from soft labels using a measureof discrepancy between contour functions -- Efficient Mo ̈bius Transformations and their applications to D-S Theory -- From shallow to deep interactions between knowledge representation, reasoning and machine learning -- Dealing with Continuous Variables in Graphical Models -- Towards Scalable and Robust Sum-Product Networks -- Learning Models over Relational Data:A Brief Tutorial -- Subspace Clustering and Some Soft Variants -- Algebraic Approximations for Weighted Model Counting. |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
13th International Conference, SUM 2019, Compiègne, France, December 16–18, 2019, Proceedings [documento electrónico] / Ben Amor, Nahla, ; Quost, Benjamin, ; Theobald, Martin, . - 1 ed. . - [s.l.] : Springer, 2019 . - XI, 452 p. 220 ilustraciones, 57 ilustraciones en color. ISBN : 978-3-030-35514-2 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Inteligencia artificial Ciencias de la Computación Informática Estadistica matematica Lógica informática y fundamentos de la programación Probabilidad y EstadÃstica en Informática |
| Clasificación: |
|
| Resumen: |
Este libro constituye las actas arbitradas de la 13.ª Conferencia Internacional sobre Gestión Escalable de la Incertidumbre, SUM 2019, que se celebró en Compiègne, Francia, en diciembre de 2019. Los 25 artÃculos completos, 4 breves, 4 tutoriales y 2 artÃculos principales invitados presentados en este volumen fueron cuidadosamente revisado y seleccionado entre 44 presentaciones. La conferencia está dedicada a la gestión de grandes cantidades de información compleja, incierta, incompleta o inconsistente. Se han desarrollado nuevos enfoques sobre probabilidades imprecisas, teorÃa de conjuntos difusos, teorÃa de conjuntos aproximados, representaciones de incertidumbre ordinal o incluso modelos puramente cualitativos. |
| Nota de contenido: |
An Experimental Study on the Behaviour of Inconsistency Measures -- Inconsistency Measurement Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study -- The Hidden Elegance of Causal Interaction Models -- Computational Models for Cumulative Prospect Theory: Application to the Knapsack Problem Under Risk -- On a new evidential C-Means algorithm with instance-level constraints -- Hybrid Reasoning on a Bipolar Argumentation Framework -- Active Preference Elicitation by Bayesian Updating on Optimality Polyhedra -- Selecting Relevant Association Rules From Imperfect Data -- Evidential classification of incomplete data via imprecise relabelling: Application to plastic sorting -- An analogical interpolation method for enlarging a training dataset -- Towards a reconciliation between reasoning and learning - A position paper -- CP-nets, π-pref nets, and Pareto dominance -- Measuring Inconsistency through Subformula Forgetting Explaining Hierarchical Multi-Linear Models -- Assertional Removed Sets Merging of DL-Lite Knowledge Bases -- An Interactive Polyhedral Approach for Multi-Objective Combinatorial Optimization with Incomplete Preference Information -- Open-Mindedness of Gradual Argumentation Semantics -- Approximate Querying on Property Graphs -- Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants -- On cautiousness and expressiveness in interval-valued logic -- Preference Elicitation with Uncertainty: Extending Regret Based Methods with Belief Functions -- Evidence Propagation and Consensus Formation in Noisy Environments -- Order-Independent Structure Learning of Multivariate Regression Chain Graphs -- l Comparison of analogy-based methods for predicting preferences -- Using Convolutional Neural Network in Cross-Domain Argumentation Mining Framework -- ConvNet and Dempster-Shafer Theory for Object Recognition -- On learning evidential contextual corrections from soft labels using a measureof discrepancy between contour functions -- Efficient Mo ̈bius Transformations and their applications to D-S Theory -- From shallow to deep interactions between knowledge representation, reasoning and machine learning -- Dealing with Continuous Variables in Graphical Models -- Towards Scalable and Robust Sum-Product Networks -- Learning Models over Relational Data:A Brief Tutorial -- Subspace Clustering and Some Soft Variants -- Algebraic Approximations for Weighted Model Counting. |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
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