Twofold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation
dc.cclicence | CC-BY-NC | en |
dc.contributor.author | Wu, Jian | |
dc.contributor.author | Wang, Sha | |
dc.contributor.author | Chiclana, Francisco | |
dc.contributor.author | Herrera-Viedma, Enrique | |
dc.date.acceptance | 2021-04-24 | |
dc.date.accessioned | 2021-04-28T14:58:45Z | |
dc.date.available | 2021-04-28T14:58:45Z | |
dc.date.issued | 2021-04 | |
dc.description | The file attached to this record is the author's final peer reviewed version. | en |
dc.description.abstract | 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. | en |
dc.funder | Other external funder (please detail below) | en |
dc.funder.other | National Natural Science Foundation of China (NSFC) | en |
dc.funder.other | Spanish State Research Agency | en |
dc.identifier.citation | Wu, J., Wang, S., Chiclana, F., Herrera-Viedma, E. (2021) Twofold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation. IEEE Transactions on Cybernetics. | en |
dc.identifier.doi | https://doi.org/10.1109/tcyb.2021.3076420 | |
dc.identifier.issn | 2168-2267 | |
dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/20808 | |
dc.language.iso | en | en |
dc.peerreviewed | Yes | en |
dc.projectid | No. 71971135, 71571166 and 71910107002 | en |
dc.projectid | PID2019-103880RBI00/AEI/10.13039/501100011033 | en |
dc.publisher | IEEEXplore | en |
dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
dc.subject | Group decision making | en |
dc.subject | Consensus | en |
dc.subject | Social network | en |
dc.subject | Uninorm interval trust propagation | en |
dc.subject | Personalized feedback | en |
dc.subject | Minimum cost | en |
dc.title | Twofold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation | en |
dc.type | Article | en |
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