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Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.

The evaluation of expert importance degree for solving group decision-making problems (GDM) is meaningful, especially for social network GDM cases. Conventionally, the importance of experts in existing GDM models is assumed to be isolated. Nevertheless, in real-life scenarios, the internal component...

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Main Authors: Liu, Zeyi, Tao, Wen, Yong, Deng, Fujita, Hamido
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Subjects:
T Technology (General)
T58.5-58.64 Information technology
Online Access:http://eprints.utm.my/108869/
http://dx.doi.org/10.1109/TETCI.2024.3372410
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spelling my.utm.1088692025-01-08T00:57:11Z http://eprints.utm.my/108869/ Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making. Liu, Zeyi Tao, Wen Yong, Deng Fujita, Hamido T Technology (General) T58.5-58.64 Information technology The evaluation of expert importance degree for solving group decision-making problems (GDM) is meaningful, especially for social network GDM cases. Conventionally, the importance of experts in existing GDM models is assumed to be isolated. Nevertheless, in real-life scenarios, the internal components of expert systems should be mutually influential. In this study, a novel game-theoretic expert importance evaluation model guided by cooperation effects is proposed. First, the framework of non-additive fuzzy measure values is utilized to obtain the initial opinions of all experts. An interaction indicator is then exploited to represent peer interaction effort (PIE). With the log-sigmoid transition technique, individual social cooperation networks (ISCNs) are then constructed. With the advanced aggregation operator, the global social cooperation network (GSCN) of the corresponding expert collection can be generated. Eventually, a modified gravity model is designed to evaluate the degree of importance for the experts. Several experiments are conducted to demonstrate the effectiveness of the proposed method. The results show that the influence of cooperation effects can reasonably be considered in the expert importance evaluation procedure, which is beneficial to real-life scenarios. Additional comparisons and related discussions are also provided. Institute of Electrical and Electronics Engineers Inc. 2024-03-19 Article PeerReviewed Liu, Zeyi and Tao, Wen and Yong, Deng and Fujita, Hamido (2024) Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making. IEEE Transactions on Emerging Topics in Computational Intelligence, 8 (4). pp. 2749-2761. ISSN 2471-285X http://dx.doi.org/10.1109/TETCI.2024.3372410 DOI:10.1109/TETCI.2024.3372410
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
T58.5-58.64 Information technology
spellingShingle T Technology (General)
T58.5-58.64 Information technology
Liu, Zeyi
Tao, Wen
Yong, Deng
Fujita, Hamido
Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
description The evaluation of expert importance degree for solving group decision-making problems (GDM) is meaningful, especially for social network GDM cases. Conventionally, the importance of experts in existing GDM models is assumed to be isolated. Nevertheless, in real-life scenarios, the internal components of expert systems should be mutually influential. In this study, a novel game-theoretic expert importance evaluation model guided by cooperation effects is proposed. First, the framework of non-additive fuzzy measure values is utilized to obtain the initial opinions of all experts. An interaction indicator is then exploited to represent peer interaction effort (PIE). With the log-sigmoid transition technique, individual social cooperation networks (ISCNs) are then constructed. With the advanced aggregation operator, the global social cooperation network (GSCN) of the corresponding expert collection can be generated. Eventually, a modified gravity model is designed to evaluate the degree of importance for the experts. Several experiments are conducted to demonstrate the effectiveness of the proposed method. The results show that the influence of cooperation effects can reasonably be considered in the expert importance evaluation procedure, which is beneficial to real-life scenarios. Additional comparisons and related discussions are also provided.
format Article
author Liu, Zeyi
Tao, Wen
Yong, Deng
Fujita, Hamido
author_facet Liu, Zeyi
Tao, Wen
Yong, Deng
Fujita, Hamido
author_sort Liu, Zeyi
title Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
title_short Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
title_full Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
title_fullStr Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
title_full_unstemmed Game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
title_sort game-theoretic expert importance evaluation model guided by cooperation effects for social network group decision making.
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2024
url http://eprints.utm.my/108869/
http://dx.doi.org/10.1109/TETCI.2024.3372410
_version_ 1821001617253597184
score 13.23648

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