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Database Mining in Spatial Databases
"... The past few years has seen an explosion in the amount of data stored in databases. Apart from textual data, there has been an increase in the amount of pictorial information being stored on computers. Within this data is a lot of implicit, potentially useful information that cannot be extracted man ..."
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Cited by 1 (0 self)
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mining in relational databases based on evidential theory [ANAN93] is extended to incorporate spatial discovery. We discuss the role of the DempsterShafer orthogonal sum combination rule in such a framework. Keywords : Database Mining, Spatial Reasoning, Evidential Theory, DempsterShafer Orthogonal Sum
Combination of evidence in DempsterShafer theory
, 2002
"... DempsterShafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. DempsterShafer theory does not require a ..."
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Cited by 81 (2 self)
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expert elicitation. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of conflict between them. This report surveys a number of possible combination rules for DempsterShafer structures and provides examples of the implementation
On combining classifiers
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1998
"... We develop a common theoretical framework for combining classifiers which use distinct pattern representations and show that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision. An experimental ..."
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Cited by 1420 (33 self)
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. An experimental comparison of various classifier combination schemes demonstrates that the combination rule developed under the most restrictive assumptions—the sum rule—outperforms other classifier combinations schemes. A sensitivity analysis of the various schemes to estimation errors is carried out to show
DempsterShafer Argument Schemes
"... Abstract. DempsterShafer theory, which can be regarded as a generalisation of probability theory, is a widely used formalism for reasoning with uncertain information. The application of the theory hinges on the use of a rule for combining evidence from different sources. A number of different comb ..."
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Abstract. DempsterShafer theory, which can be regarded as a generalisation of probability theory, is a widely used formalism for reasoning with uncertain information. The application of the theory hinges on the use of a rule for combining evidence from different sources. A number of different
A defect in DempsterShafer theory
 InProceedings of the Tenth Conference on Uncertainty in Arti cial Intelligence
, 1994
"... By analyzing the relationships among chance, weight of evidence and degree ofbelief, it is shown that the assertion \chances are special cases of belief functions " and the assertion \Dempster's rule can be used to combine belief functions based on distinct bodies of evidence " togeth ..."
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Cited by 28 (20 self)
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By analyzing the relationships among chance, weight of evidence and degree ofbelief, it is shown that the assertion \chances are special cases of belief functions " and the assertion \Dempster's rule can be used to combine belief functions based on distinct bodies of evidence "
The Combining Rule of DempsterShafer Theory for Correlative Evidence
"... This paper puts forward an improvement method for the combining rule of DempsterShafer evidence theory based on the correlation between evidences. Different from DS theory, the correlation coefficient between evidences is introduced. By decreasing the probability evaluation of certainty and increa ..."
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This paper puts forward an improvement method for the combining rule of DempsterShafer evidence theory based on the correlation between evidences. Different from DS theory, the correlation coefficient between evidences is introduced. By decreasing the probability evaluation of certainty
A GENERALIZATION OF THE DEMPSTERSHAFER THEORY
"... The DempsterShafer theory gives a solid basis for reasoning applications characterized by uncertainty. A key feature of the theory is that propositions are represented as subsets of a set which represents a hypothesis space. This power set along with the set operations is a Boolean algebra. Can we ..."
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be enhanced. In a previous paper we generalized the DempsterShafer orthogonal sum operation to support practical evidence pooling. In the present paper we provide the theoretical underpinning of that procedure, by systematically considering familiar evidential functions in turn. For each we present a &
DempsterShafer Theory Approach to FMEA
"... Abstract Failure Mode and Effects Analysis (FMEA) technique is a group based activity to prioritize risk. Often times there are issues with aggregating team member's responses or ratings. Literature suggests several means to aggregate these responses computing average values, using group cons ..."
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. The aforementioned aggregation techniques have been used with very limited success in such uncertain instances. This paper will propose a method that utilizes DempsterShafer Theory (DST) to overcome these issues. It will be shown that DST will allow unbiased aggregation of team member's ratings using rules
A Simple View of the DempsterShafer Theory of Evidence and its Implication for the Rule of Combination
 AI Magazine
, 1986
"... The emergence of expert systems as one of the major areas of activity within AI has resulted in a rapid growth of interest within the AI community in issues relating to the management of uncertainty and evidential reasoning. During the past two years, in particular, the DempsterShafer theory of e ..."
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Cited by 114 (0 self)
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The emergence of expert systems as one of the major areas of activity within AI has resulted in a rapid growth of interest within the AI community in issues relating to the management of uncertainty and evidential reasoning. During the past two years, in particular, the DempsterShafer theory
A MonteCarlo Algorithm for DempsterShafer Belief
 Proc. 7th Conference on Uncertainty in Articial Intelligence
, 1991
"... A very computationallyefficient MonteCarlo algorithm for the calculation of DempsterShafer belief is described. If Bel is the combination using Dempster’s Rule of belief functions Bel1,..., Belm then, for subset b of the frame Θ, Bel(b) can be calculated in time linear in Θ  and m (given that t ..."
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Cited by 18 (3 self)
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A very computationallyefficient MonteCarlo algorithm for the calculation of DempsterShafer belief is described. If Bel is the combination using Dempster’s Rule of belief functions Bel1,..., Belm then, for subset b of the frame Θ, Bel(b) can be calculated in time linear in Θ  and m (given
Results 1  10
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