Belief Functions: Theory and Applications

1. Front Matter

   Pages I-XI

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2. An Evidential Collaborative Filtering Approach Based on Items Contents Clustering

   • Raoua Abdelkhalek, Imen Boukhris, Zied Elouedi

   Pages 1-9

3. The Belief Functions Theory for Sensors Localization in Indoor Wireless Networks

   • Daniel Alshamaa, Farah Mourad-Chehade, Paul Honeine

   Pages 10-13

4. On Evidential Clustering with Partial Supervision

   • Violaine Antoine, Kévin Gravouil, Nicolas Labroche

   Pages 14-21

5. Exploiting Domain-Experts Knowledge Within an Evidential Process for Case Base Maintenance

   • Safa Ben Ayed, Zied Elouedi, Eric Lefevre

   Pages 22-30

6. The Kantorovich Problem and Wasserstein Metric in the Theory of Belief Functions

   • Andrey G. Bronevich, Igor N. Rozenberg

   Pages 31-38

7. Generalised Max Entropy Classifiers

   • Fabio Cuzzolin

   Pages 39-47

8. General Geometry of Belief Function Combination

   • Fabio Cuzzolin

   Pages 48-56

9. Logistic Regression Revisited: Belief Function Analysis

   • Thierry Denoeux

   Pages 57-64

10. From Relations Between Sets to Relations Between Belief Functions

    • Sébastien Destercke, Frédéric Pichon, John Klein

    Pages 65-72

11. Application of Belief Functions to Levee Assessment

    • Théo Dezert, Yannick Fargier, Sérgio Palma Lopes, Philippe Côte

    Pages 73-76

12. Prejudiced Information Fusion Using Belief Functions

    • Didier Dubois, Francis Faux, Henri Prade

    Pages 77-85

13. A Heuristic Approach for the Robust Flight Level Assignment Problem

    • Akli Fundo, Dritan Nace, Chenghao Wang

    Pages 86-94

14. Study of Distributed Data Fusion Using Dempster’s Rule and Cautious Operator

    • Romain Guyard, Véronique Cherfaoui

    Pages 95-102

15. Uncertainty-Aware Parzen-Rosenblatt Classifier for Multiattribute Data

    • Ali Hamache, Mohamed El Yazid Boudaren, Houdaifa Boukersoul, Islam Debicha, Hamza Sadouk, Rezki Zibani et al.

    Pages 103-111

16. Birnbaum’s Importance Measure Extended for Non-coherent Systems

    • Ayyoub Imakhlaf, Mohamed Sallak

    Pages 112-120

17. Evidential Independence Maximization on Twitter Network

    • Siwar Jendoubi, Mouna Chebbah, Arnaud Martin

    Pages 121-128

18. An Evidential k-nearest Neighbors Combination Rule for Tree Species Recognition

    • Siwar Jendoubi, Didier Coquin, Reda Boukezzoula

    Pages 129-136

19. A Compact Belief Rule-Based Classification System with Evidential Clustering

    • Lianmeng Jiao, Xiaojiao Geng, Quan Pan

    Pages 137-145

20. A Decomposable Entropy of Belief Functions in the Dempster-Shafer Theory

    • Radim Jiroušek, Prakash P. Shenoy

    Pages 146-154

This book constitutes the refereed proceedings of the 5th International Conference on Belief Functions, BELIEF 2018, held in Compiègne, France, in September 2018.The 33 revised regular papers presented in this book were carefully selected and reviewed from 73 submissions. The papers were solicited on theoretical aspects (including for example statistical inference, mathematical foundations, continuous belief functions) as well as on applications in various areas including classification, statistics, data fusion, network analysis and intelligent vehicles.

• uncertainty quantification
• fuzzy sets
• belief functions
• imprecise probabilities
• machine learning
• imprecision
• data science
• statistics
• graphical models
• information fusion
• uncertainty analysis
• sensors
• problem solving
• classification

• University of Technology of Compiègne, Compiègne Cedex, France

  Sébastien Destercke

• UMR CNRS 7253 Heudiasyc, Université de Technologie de Compiègne, Compiègne Cedex, France

  Thierry Denoeux

• Department of Computing and Communication, Oxford Brookes University, Oxford, United Kingdom

  Fabio Cuzzolin

• Université de Rennes 1, Lannion Cedex, France

  Arnaud Martin

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