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Group Decision and Negotiation

Erschienen in:

27.06.2023

Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making

verfasst von: Phan-Anh-Huy Nguyen, Ping-Yu Hsu

Erschienen in: Group Decision and Negotiation | Ausgabe 5/2023

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Abstract

With the advancement of online technologies in recent years, crowdsourcing data has been used for numerous applications in many fields. The preference sequences obtained through crowdsourcing are valuable resources for ranking. However, the aggregation of incomplete and inconsistent preferences is complicated. To address these challenges, this study proposed a novel method termed robust crowd ranking (RCR) based on a consistent fuzzy c-means approach to increase the robustness and accessibility of aggregated preference sequences obtained through crowdsourcing. To verify the robustness, accessibility, and accuracy of RCR, comprehensive experiments were conducted using synthetic and real data. The simulation results validated that the RCR outperforms Borda Count, Dodgson, IRV and Tideman methods.

Vorheriger Artikel Analysis of Security Threats in the Supply Chain of ICT Products Based on Evolutionary Game Theory

Nächster Artikel Coming to Consensus on Classification in Flexible Linguistic Preference Relations: The Role of Personalized Individual Semantics

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Titel: Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making
verfasst von: Phan-Anh-Huy Nguyen
Ping-Yu Hsu
Publikationsdatum: 27.06.2023
Verlag: Springer Netherlands
Erschienen in: Group Decision and Negotiation / Ausgabe 5/2023
Print ISSN: 0926-2644
Elektronische ISSN: 1572-9907
DOI: https://doi.org/10.1007/s10726-023-09840-2

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