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Belief Functions: Theory and Applications

5th International Conference, BELIEF 2018, Compiègne, France, September 17-21, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Sébastien Destercke

    1. University of Technology of Compiègne, Compiègne Cedex, France

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  2. Thierry Denoeux

    1. UMR CNRS 7253 Heudiasyc, Université de Technologie de Compiègne, Compiègne Cedex, France

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  3. Fabio Cuzzolin

    1. Department of Computing and Communication, Oxford Brookes University, Oxford, United Kingdom

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  4. Arnaud Martin

    1. Université de Rennes 1, Lannion Cedex, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11069)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: BELIEF 2018.

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About this book

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.

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Keywords

Table of contents (33 papers)

  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
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Other volumes

  1. Belief Functions: Theory and Applications

Editors and Affiliations

  • 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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