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Ranking fuzzy values with satisfaction function [PDF]
Fuzzy Sets and Systems, 1994 This paper proposes a measure called the satisfaction function which estimates the satisfaction degree of arithmetic comparison relations (such as >, <, =) between two fuzzy values.
Keon Myung Lee +2 more
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Revision by Comparison for Ranking Functions
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022Revision by Comparison (RbC) is a non-prioritized belief revision mechanism on epistemic states that specifies constraints on the plausibility of an input sentence via a designated reference sentence, allowing for kind of relative belief revision. In this paper, we make the strategy underlying RbC more explicit and transfer the mechanism together with ...
Meliha Sezgin, Gabriele Kern-Isberner
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Rankings and Ranking Functions
Canadian Journal of Mathematics, 1981Suppose that n competitors compete in r races and in each race they are awarded placings l, 2, 3, …, n – 1, n. After the r races each competitor has a result consisting of his r placings. Let such a result be written (αj)1≦j≦r where for convenience the positive integers αj are arranged in ascending order.
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Order, 2005
The authors describe the correspondence between closure operators \(\text{cl}: D \to D\) and \(\land\)-subsemilattices \(L \subseteq D\) where \(D\) is a lattice of finite height. They investigate what type of number-valued function \(D \to N\) induces a \(\land\)-subsemilattice \(L\) and, conversely, what type of function \(D \to N\) is induced by ...
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The authors describe the correspondence between closure operators \(\text{cl}: D \to D\) and \(\land\)-subsemilattices \(L \subseteq D\) where \(D\) is a lattice of finite height. They investigate what type of number-valued function \(D \to N\) induces a \(\land\)-subsemilattice \(L\) and, conversely, what type of function \(D \to N\) is induced by ...
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Construct Weak Ranking Functions for Learning Linear Ranking Function
2011Many Learning to Rank models, which apply machine learning techniques to fuse weak ranking functions and enhance ranking performances, have been proposed for web search. However, most of the existing approaches only apply the Min --- Max normalization method to construct the weak ranking functions without considering the differences among the ranking ...
Guichun Hua +4 more
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A contest success function for rankings [PDF]
Social Choice and Welfare, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Discovery and Ranking of Functional Dependencies
2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019Computing the functional dependencies that hold on a given data set is one of the most important problems in data profiling. Utilizing new data structures and original techniques for the dynamic computation of stripped partitions, we devise a new hybridization strategy that outperforms the best algorithms in terms of efficiency, column-, and row ...
Ziheng Wei, Sebastian Link
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Generalized subdifferentials of the rank function
Optimization Letters, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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LEG Networks for Ranking Functions
2014When using representations of plausibility for semantical frameworks, the storing capacity needed is usually exponentially in the number of variables. Therefore, network-based approaches that decompose the semantical space have proven to be fruitful in environments with probabilistic information. For applications where a more qualitative information is
Christian Eichhorn 0001 +1 more
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Ranking fuzzy numbers with preference weighting function expectations [PDF]
Computers and Mathematics With Applications, 2005 Based on the recent research developments of fuzzy number ranking, the paper extends the centroid expectation approach and proposes a preference weighting function expectation method to rank fuzzy numbers.
Liu, Xin-Wang, Han, Shi-Lian
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