Clustering interval-valued proximity data using belief functions
Pattern Recognition Letters
Analyzing the combination of conflicting belief functions
Information Fusion
Multi-camera people tracking using evidential filters
International Journal of Approximate Reasoning
Possibilistic evidential clustering
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Belief Functions and Cluster Ensembles
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Possibilistic Similarity Estimation and Visualization
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
Imperfect pattern recognition using the fuzzy measure theory
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Fusion of possibilistic sources of evidences for pattern recognition
Integrated Computer-Aided Engineering
International Journal of Approximate Reasoning
DK-BKM: decremental K belief K-modes method
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Ranking-based feature selection method for dynamic belief clustering
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
A novel approach for meeting the challenges of the integrated security systems
WSEAS TRANSACTIONS on SYSTEMS
Distances in evidence theory: Comprehensive survey and generalizations
International Journal of Approximate Reasoning
EDTs: evidential decision trees
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
CECM: Constrained evidential C-means algorithm
Computational Statistics & Data Analysis
A new belief-based K-nearest neighbor classification method
Pattern Recognition
Robust kernelized approach to clustering by incorporating new distance measure
Engineering Applications of Artificial Intelligence
Evidential classifier for imprecise data based on belief functions
Knowledge-Based Systems
Information-based dissimilarity assessment in Dempster-Shafer theory
Knowledge-Based Systems
International Journal of Approximate Reasoning
An extension to Rough c-means clustering based on decision-theoretic Rough Sets model
International Journal of Approximate Reasoning
A choice model with imprecise ordinal evaluations
International Journal of Approximate Reasoning
A belief classification rule for imprecise data
Applied Intelligence
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A new relational clustering method is introduced, based on the Dempster-Shafer theory of belief functions (or evidence theory). Given a matrix of dissimilarities between n objects, this method, referred to as evidential clustering (EVCLUS), assigns a basic belief assignment (or mass function) to each object in such a way that the degree of conflict between the masses given to any two objects reflects their dissimilarity. A notion of credal partition is introduced, which subsumes those of hard, fuzzy, and possibilistic partitions, allowing to gain deeper insight into the structure of the data. Experiments with several sets of real data demonstrate the good performances of the proposed method as compared with several state-of-the-art relational clustering techniques.