The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A new distance between two bodies of evidence
Overview
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Registry
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Statistics
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Citations
Cites
A Mathematical Theory of Evidence
Shafer, G. (2020) · Princeton University Press eBooks · doi:10.2307/j.ctv10vm1qb · Cited by 11,711
Upper and Lower Probabilities Induced by a Multivalued Mapping
Dempster, A. P. (1967) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177698950 · Cited by 6,126
Upper and Lower Probabilities Induced by a Multivalued Mapping
Dempster, A. P. (2008) · Studies in Fuzziness and Soft Computing · doi:10.1007/978-3-540-44792-4_3 · Cited by 5,296
Smets, P., & Kennes, R. (1994) · Artificial Intelligence · doi:10.1016/0004-3702(94)90026-4 · Cited by 2,216
A mathematical theory of evidence
Rota, G. (1977) · Advances in Mathematics · doi:10.1016/0001-8708(77)90069-x · Cited by 1,802
The combination of evidence in the transferable belief model
Smets, P. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.55104 · Cited by 1,113
Constructing the Pignistic Probability Function in a Context of Uncertainty
(1990) · Machine Intelligence and Pattern Recognition · doi:10.1016/b978-0-444-88738-2.50010-5 · Cited by 433
On random sets and belief functions
Nguyen, H. T. (1978) · Journal of Mathematical Analysis and Applications · doi:10.1016/0022-247x(78)90161-0 · Cited by 333
An evidence-theoretic k-NN rule with parameter optimization
Zouhal, L. M., & Denoeux, T. (1998) · IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/5326.669565 · Cited by 296
Approximations for efficient computation in the theory of evidence
Tessem, B. (1993) · Artificial Intelligence · doi:10.1016/0004-3702(93)90072-j · Cited by 234
Cited by
Combining belief functions based on distance of evidence
Yong, D., WenKang, S., ZhenFu, Z., & Qi, L. (2004) · Decision Support Systems · doi:10.1016/j.dss.2004.04.015 · Cited by 579
A survey: Optimization and applications of evidence fusion algorithm based on Dempster–Shafer theory
Zhao, K., Li, L., Chen, Z., Sun, R., Yuan, G., & Li, J. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109075 · Cited by 150
Metadata
- Authors
- Jousselme, A.-L., Grenier, D., & Bossé, É.
- Venue
- Information Fusion
- Publisher
- Elsevier BV
- Published
- 2001-06
- Volume
- 2
- Issue
- 2
- Pages
- 91-101
- ISSN
- 1566-2535 (ISSN-L)
- OpenAlex
- W1993853885
- Cited by
- 932
- References
- 11
- FWCI
- 2.77
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
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- This page
- CoChat. (2026). Citation check: A new distance between two bodies of evidence. https://app.cochat.ai/papers/10.1016/s1566-2535(01)00026-4
- The paper
- Jousselme, A.-L., Grenier, D., & Bossé, É. (2001). A new distance between two bodies of evidence. Information Fusion. https://doi.org/10.1016/s1566-2535(01)00026-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
