A Generalized Decision Logic in Interval-Set-Valued Information Tables

Yao, Yiyu; Liu, Qing

doi:10.1007/978-3-540-48061-7_35

Cited by 39 publications

(14 citation statements)

References 12 publications

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“…In contrast, the operation of decomposing a granule into a set of smaller granules is referred to as decomposition. [7,8] The process in which a group of objects interact with each other to perform a specific task is referred to as computing with granules.…”

Section: Figure1 a Concept Hierarchy Of 0-n Granule Levelsmentioning

confidence: 99%

On Modeling Data Mining with Time Granularity

Zhong

2009

2009 International Conference on Computational Intelligence and Natural Computing

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Granular Computing (GrC) is an umbrella term to cover any theory, methodology, technique and tool that makes usage of granules in the complex problem solving and provides an effective method for massive data-mining in huge data warehouse system. This paper presents a time granularity model firstly and then put the time granularity in applications which can reflect Granular Computing(GrC) mining at different times levels.

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Section: Figure1 a Concept Hierarchy Of 0-n Granule Levelsmentioning

confidence: 99%

On Modeling Data Mining with Time Granularity

Zhong

2009

2009 International Conference on Computational Intelligence and Natural Computing

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“…This presents a generalization of set-valued information tables. Yao and Liu [51] introduced a generalized decision logic for interval-set-valued information tables.…”

Section: Studies Related To Interval Setsmentioning

confidence: 99%

Interval sets and interval-set algebras

Yao

2009

2009 8th IEEE International Conference on Cognitive Informatics

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An interval set is an interval in the power set lattice based on a universal set and is a family of subsets of the universal set. Interval sets and interval-set algebras provide a tool for modeling and processing partially known concepts and for approximating undefinable or complex concepts. Existing results on interval sets and interval-set algebras are reviewed and new results are given. Two types of interval-set algebras are examined based on an inclusion ordering and a knowledge ordering, respectively. Related studies are summarized.

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“…Yao [21] presented a model for the interval set by using the lower and upper approximations. Yao and Liu [23] introduced the generalized decision logic in interval-set-valued information tables which is an extension of decision logic studied by Pawlak. Leung et ale [2] defined the concept of misclassification rates and discovered the classification rules from the interval-valued information systems.…”

Section: Introductionmentioning

confidence: 99%

“…Due to rampant existence of interval numbers in information systems in real life, the research on combination of rough sets and interval numbers becomes necessary [21][22][23]. Yao [21] presented a model for the interval set by using the lower and upper approximations.…”

Section: Introductionmentioning

confidence: 99%

Knowledge reduction in interval-valued information systems

Miao

Zhang

Yue

2009

2009 8th IEEE International Conference on Cognitive Informatics

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In this paper, the concept of a -maximal consistent blocks is proposed to formulate the new rough approximations to an arbitrary object set in intervalvalued information systems. The a -maximal consistent blocks can provide the simpler discernibility matrices and discemibility functions in reduction of intervalvalued information systems. This means that they can provide a more efficient computation for knowledge acquisitions. Numerical examples are employed to substantiate the conceptual arguments.

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A Generalized Decision Logic in Interval-Set-Valued Information Tables

Cited by 39 publications

References 12 publications

On Modeling Data Mining with Time Granularity

On Modeling Data Mining with Time Granularity

Interval sets and interval-set algebras

Knowledge reduction in interval-valued information systems

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