The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Tsung-chun Tsai - One of the best experts on this subject based on the ideXlab platform.
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Crowdsourcing techniques to create a Fuzzy Subset of SNOMED CT for semantic tagging of medical documents
Soft Computing, 2012Co-Authors: David T. Parry, Tsung-chun TsaiAbstract:Ontologies and other schemes are useful for allowing semantic tagging of documents for many applications on the semantic web. Representing uncertainty on the semantic web is becoming increasingly common, using ontologies and other techniques. Ontology and declarative tools allow documents using concepts contained in these ontologies to be reasoned about using computer systems. Very large ontologies and vocabularies have been created; however, users may find it difficult to select the correct concept or term when there are large numbers of items that on face value appear to represent the same idea. Creating Subsets of ontologies is a popular approach to solve this problem but this may not fit well with the need to deal with complex domains. However, crowdsourcing techniques, which harness the power of large groups, may be more effective than document analysis or expert opinion. In crowdsourcing, large numbers of people collaborate by performing relatively simple tasks usually using applications distributed via the World Wide Web. This approach is being tested in the medical domain using a very large clinical vocabulary, SNOMED CT.
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crowdsourcing techniques to create a Fuzzy Subset of snomed ct for semantic tagging of medical documents
IEEE International Conference on Fuzzy Systems, 2010Co-Authors: David Parry, Tsung-chun TsaiAbstract:Ontologies and other schemes are useful for allowing semantic tagging of documents for many applications on the semantic web. Representing uncertainty on the semantic web is becoming increasingly common, using Fuzzy ontologies and other techniques. Very large ontologies and vocabularies have been created, however users may find it difficult to select the correct concept or term when there are large numbers of items that on face value appear to represent the same idea. Creating Subsets of ontologies is a popular approach to solving this problem but this may not fit well with the need to deal with complex domains. However crowdsourcing techniques, which harness the power of large groups, may be more effective than document analysis or expert opinion. In Crowdsourcing, large numbers of people collaborate by performing relatively simple tasks usually using applications distributed via the World Wide Web. This approach is being tested in the medical domain using a very large clinical vocabulary, SNOMED CT.
Hui Dong - One of the best experts on this subject based on the ideXlab platform.
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uncertain context modeling of dimensional ontology using Fuzzy Subset theory
Scalable Uncertainty Management, 2008Co-Authors: Ying Jiang, Hui DongAbstract:Context-sensitive knowledge is widespread in Semantic Web, but traditional RDF triples lack references to situations, points in time, or generally contexts. In order to resolve this problem, Dimensional Ontology (DO) theory is put forward, which features dimensional relations, dimensional operators as well as reasoning mechanism for context-sensitive knowledge. The notion of context in DO is actuarially a vector of dimensions, which are crisp sets representing certain contextual aspects. We propose an approach of modeling uncertain contexts of DO through Fuzzy Subsets instead of crisp ones. In this way, DO provides the ability of representing Fuzzy triples in uncertain contexts. Apart from describing uncertain context model of DO, we discuss how dimensional operators and reasoning mechanism can be applied to uncertain contexts to allow more complex manipulations.
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SUM - Uncertain Context Modeling of Dimensional Ontology Using Fuzzy Subset Theory
Lecture Notes in Computer Science, 2008Co-Authors: Ying Jiang, Hui DongAbstract:Context-sensitive knowledge is widespread in Semantic Web, but traditional RDF triples lack references to situations, points in time, or generally contexts. In order to resolve this problem, Dimensional Ontology (DO) theory is put forward, which features dimensional relations, dimensional operators as well as reasoning mechanism for context-sensitive knowledge. The notion of context in DO is actuarially a vector of dimensions, which are crisp sets representing certain contextual aspects. We propose an approach of modeling uncertain contexts of DO through Fuzzy Subsets instead of crisp ones. In this way, DO provides the ability of representing Fuzzy triples in uncertain contexts. Apart from describing uncertain context model of DO, we discuss how dimensional operators and reasoning mechanism can be applied to uncertain contexts to allow more complex manipulations.
Bin Zhao - One of the best experts on this subject based on the ideXlab platform.
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Q-Fuzzy Subsets on ordered semigroups
Fuzzy Sets and Systems, 2013Co-Authors: Shengwei Han, Bin ZhaoAbstract:In this paper, we introduce the concept of a Q-Fuzzy Subset of an ordered semigroup where a quantale Q replaces the unit interval. We define a binary operation on the Fuzzy power set that makes it a quantale. In order to discuss the relation between the referential set and the Fuzzy power set, the notion of an ordered Q-Fuzzy point of an ordered semigroup is introduced. In terms of ordered Q-Fuzzy points, we prove that any ordered semigroup can be embedded into a quantale, and also build a functor between the category of ordered semigroups and the category of quantales.
Ronald R Yager - One of the best experts on this subject based on the ideXlab platform.
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Extending Set Measures to Pythagorean Fuzzy Sets
International Journal of Fuzzy Systems, 2019Co-Authors: Ronald R YagerAbstract:We introduce the idea of level sets which are crisp sets associated with a Fuzzy set. We show how we can represent a Fuzzy set using a collection of level sets; this allows us to extend set functions, such as probability and other set measures, to Fuzzy Subsets. We emphasize that this extension is itself a Fuzzy Subset. We next introduce Pythagorean Fuzzy Subsets and discuss the OWA and Choquet aggregation of these sets. We provide a formulation for level sets associated with a Pythagorean Fuzzy Subset that we use to provide a representation of a Pythagorean Fuzzy set in terms of level sets. With the aid of Zadeh’s extension principle, we use this level set representation to provide for an extension of set measures to Pythagorean Fuzzy sets. We then suggest an alternative approach to extending set measures to Pythagorean Fuzzy sets using the Choquet integral.
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On Viewing Fuzzy Measures as Fuzzy Subsets
IEEE Transactions on Fuzzy Systems, 2016Co-Authors: Ronald R YagerAbstract:We introduce the concept of a Fuzzy measure, discuss some of their basic properties and look at some notable examples. We introduce a correspondence between a Fuzzy measure on X and a Fuzzy Subset over the power set of X. These Fuzzy Subsets are required to have special properties on the space 2X and we refer to these as measure type Fuzzy sets. We take advantage of this correspondence between a Fuzzy measure and a Fuzzy set to suggest the formulation of various set operations on Fuzzy measures
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Probability measures over Fuzzy spaces
International Journal of General Systems, 2007Co-Authors: Ronald R YagerAbstract:A probability measure is defined on Subsets of an underlying space. In classical probability theory, both the underlying space and the Subsets whose probabilities we measure are crisp Subsets. Zadeh provided an extension of this to the case in which the Subsets whose probabilities we are measuring can be Fuzzy. Here, we provide a further generalization of the idea of a probability measure to the case in which the underlying space itself can be a Fuzzy Subset. In addition to providing a method for determining the probabilities of Subsets in this more general environment, we provide a definition for the entropy associated with this type of distribution.
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Element selection from a Fuzzy Subset using the Fuzzy integral
IEEE Transactions on Systems Man and Cybernetics, 1993Co-Authors: Ronald R YagerAbstract:The problem of selecting a crisp element based upon a Fuzzy set is investigated. It is noted that the defuzzification problem in Fuzzy logic control is a special case of this problem. The given Fuzzy Subset is considered as a set of pieces of advice where the strengths of the advice is the membership grade. This problem is formulated in terms of a generalized expected value, an aggregation problem, by using the Fuzzy integral. Ways to convert the Fuzzy set into a Fuzzy measure are shown. Different structures for the calculation of best action are developed. >
David Parry - One of the best experts on this subject based on the ideXlab platform.
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crowdsourcing techniques to create a Fuzzy Subset of snomed ct for semantic tagging of medical documents
IEEE International Conference on Fuzzy Systems, 2010Co-Authors: David Parry, Tsung-chun TsaiAbstract:Ontologies and other schemes are useful for allowing semantic tagging of documents for many applications on the semantic web. Representing uncertainty on the semantic web is becoming increasingly common, using Fuzzy ontologies and other techniques. Very large ontologies and vocabularies have been created, however users may find it difficult to select the correct concept or term when there are large numbers of items that on face value appear to represent the same idea. Creating Subsets of ontologies is a popular approach to solving this problem but this may not fit well with the need to deal with complex domains. However crowdsourcing techniques, which harness the power of large groups, may be more effective than document analysis or expert opinion. In Crowdsourcing, large numbers of people collaborate by performing relatively simple tasks usually using applications distributed via the World Wide Web. This approach is being tested in the medical domain using a very large clinical vocabulary, SNOMED CT.
