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Related papers: Evidence as Opinions of Experts

200 papers

In this paper a new mathematical procedure is presented for combining different pieces of evidence which are represented in the interval form to reflect our knowledge about the truth of a hypothesis. Evidences may be correlated to each…

Artificial Intelligence · Computer Science 2013-04-05 L. W. Chang , Rangasami L. Kashyap

This paper presents a new classifier combination technique based on the Dempster-Shafer theory of evidence. The Dempster-Shafer theory of evidence is a powerful method for combining measures of evidence from different classifiers. However,…

Artificial Intelligence · Computer Science 2011-07-04 A. Al-Ani , M. Deriche

The Dempster-Shafer theory of evidence accumulation is one of the main tools for combining data obtained from multiple sources. In this paper a special case of combination of two bodies of evidence with non-zero conflict coefficient is…

Probability · Mathematics 2011-07-04 Andrzej K. Brodzik , Robert H. Enders

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is…

Artificial Intelligence · Computer Science 2017-04-07 Mieczysław Kłopotek

To develop an approach to utilizing continuous statistical information within the Dempster- Shafer framework, we combine methods proposed by Strat and by Shafero We first derive continuous possibility and mass functions from…

Artificial Intelligence · Computer Science 2013-04-12 Pascal Fua

The combination of evidence in Dempster-Shafer theory is compared with the combination of evidence in probabilistic logic. Sufficient conditions are stated for these two methods to agree. It is then shown that these conditions are minimal…

Artificial Intelligence · Computer Science 2013-04-11 Daniel Hunter

Dempster-Shafer evidence theory has been widely used in various fields of applications, because of the flexibility and effectiveness in modeling uncertainties without prior information. However, the existing evidence theory is insufficient…

Artificial Intelligence · Computer Science 2019-06-28 Fuyuan Xiao

Dempster-Shafer evidence theory is a powerful tool in information fusion. When the evidence are highly conflicting, the counter-intuitive results will be presented. To adress this open issue, a new method based on evidence distance of…

Artificial Intelligence · Computer Science 2014-04-21 Hongming Mo , Yong Deng

The paper presents a novel view of the Dempster-Shafer belief function as a measure of diversity in relational data bases. It is demonstrated that under the interpretation The Dempster rule of evidence combination corresponds to the join…

Artificial Intelligence · Computer Science 2017-04-11 Mieczysław A. Kłopotek , Sławomir T. Wierzchoń

The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang

This paper investigates the issues of combination and normalization of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence. Existing approaches are reviewed and thoroughly analyzed. The advantages…

Artificial Intelligence · Computer Science 2020-11-30 Miao Qin , Yongchuan Tang

While Evidence Theory (also known as Dempster-Shafer Theory, or Belief Functions Theory) is being increasingly used in data fusion, its potentialities in the Social and Life Sciences are often obscured by lack of awareness of its…

Artificial Intelligence · Computer Science 2025-03-31 Guido Fioretti

Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning…

Artificial Intelligence · Computer Science 2013-06-13 Catarina Moreira , Andreas Wichert

We discuss the Dempster-Shafer theory of evidence. We introduce a concept of monotonicity which is related to the diminution of the range between belief and plausibility. We show that the accumulation of knowledge in this framework exhibits…

Artificial Intelligence · Computer Science 2013-04-08 Ronald R. Yager

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and…

Artificial Intelligence · Computer Science 2017-03-16 Xinyang Deng , Wen Jiang

One problem to solve in the context of information fusion, decision-making, and other artificial intelligence challenges is to compute justified beliefs based on evidence. In real-life examples, this evidence may be inconsistent,…

Artificial Intelligence · Computer Science 2023-06-07 Daira Pinto Prieto , Ronald de Haan , Aybüke Özgün

In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to…

Artificial Intelligence · Computer Science 2013-04-12 Lotfi Zadeh , Anca Ralescu

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis…

Artificial Intelligence · Computer Science 2014-05-14 Yong Deng

An evidential reasoning mechanism based on the Dempster-Shafer theory of evidence is introduced. Its performance in real-world image analysis is compared with other mechanisms based on the Bayesian formalism and a simple weight combination…

Computer Vision and Pattern Recognition · Computer Science 2013-04-11 Ze-Nian Li

In Dempster-Shafer belief theory, general beliefs are expressed as belief mass distribution functions over frames of discernment. In Subjective Logic beliefs are expressed as belief mass distribution functions over binary frames of…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang
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