Two-Fold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation
| Autor: | Jian Wu, Sha Wang, Francisco Chiclana, Enrique Herrera-Viedma |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
0209 industrial biotechnology
Consensus Computer science Decision Making Rationality 02 engineering and technology Interval (mathematics) Trust Machine learning computer.software_genre Trust relationship Feedback Social Networking Uninorm interval trust propagation Group decision making 020901 industrial engineering & automation Operator (computer programming) 0202 electrical engineering electronic engineering information engineering Humans Electrical and Electronic Engineering Social network Mechanism (biology) business.industry Computer Science Applications Group decision-making Human-Computer Interaction Minimum cost Control and Systems Engineering 020201 artificial intelligence & image processing Artificial intelligence business computer Advice (complexity) Personalized feedback Software Information Systems |
| Zdroj: | IEEE Transactions on Cybernetics. 52:11081-11092 |
| ISSN: | 2168-2275 2168-2267 |
| DOI: | 10.1109/tcyb.2021.3076420 |
| Popis: | The file attached to this record is the author's final peer reviewed version. A twofold personalized feedback mechanism is established for consensus reaching in social network group decision making (SN-GDM). It consists of two stages: (1) generating the trusted recommendation advice for individuals; and (2) producing personalized adoption coefficient for reducing unnecessary adjustment costs. This is achieved by means of a uninorm interval-valued trust propagation operator to obtain indirect trust. The trust relationship is used to generate personalized recommendation advice based on the principle of ‘a recommendation being more acceptable the higher the level of trust it derives from’. An optimization model is built to minimise the total adjustment cost of reaching consensus by determining personalized feedback adoption coefficient based on individuals’ consensus levels. Consequently, the proposed twofold personalized feedback mechanism achieves a balance between group consensus and individual personality. An example to demonstrate how the proposed twofold personalized feedback mechanism works is included, which is also used to show its rationality by comparison with the traditional feedback mechanism in GDM. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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