dc.contributor.author |
Peters, James Francis |
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dc.contributor.author |
Ramanna, Sheela |
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dc.date.accessioned |
2023-01-27T08:22:38Z |
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dc.date.available |
2023-01-27T08:22:38Z |
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dc.date.issued |
2016 |
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dc.identifier.issn |
0950-7051 |
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dc.identifier.uri |
http://dspace.adiyaman.edu.tr:8080/xmlui/handle/20.500.12414/4374 |
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dc.description.abstract |
This article introduces proximal three-way decision-making. This form of 3-way decision-making stems from the proximity structures that result from endowing each nonempty set of social network triangulation nodes with several proximity relations. A triangulation is obtained by connecting every pair of nearest neighbour nodes with a straight edge. The proposed approach to 3-way decision-making results from the analysis of Delaunay graphs (spatial) as well as friendship network (social) of location-based social network nodes. The knowledge gained from proximal three-way decision-making is in the form of information granules that are near sets of nodes representing interaction between either casual users or friends in a social network. A practical illustration of proximal three-way decision-making is given in terms of a public domain large-scale social network dataset. (C) 2015 Elsevier B.V. All rights reserved. |
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dc.language.iso |
en |
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dc.publisher |
Elsevier |
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dc.subject |
Delaunay triangulation |
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dc.subject |
Proximity |
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dc.subject |
Three-way decisions |
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dc.subject |
Nearness of sets |
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dc.subject |
Social networks |
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dc.title |
Proximal three-way decisions: Theory and applications in social networks |
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dc.type |
Article |
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dc.contributor.department |
Univ Manitoba, Computat Intelligence Lab, |
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dc.contributor.department |
Adiyaman Univ, Dept Math, |
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dc.contributor.department |
Univ Winnipeg, Appl Comp Sci, Winnipeg |
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dc.identifier.endpage |
15 |
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dc.identifier.startpage |
4 |
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dc.identifier.volume |
91 |
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dc.source.title |
Knowledge-Based Systems |
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