A Trustworthiness-Aware Spatial Task Allocation using a Fuzzy-based Trust and Reputation System Approach
作者：
Highlights：
• A framework computes workers trustworthiness based on trust and reputation factors.
• It produces a degree of trustworthiness score for a fairer decision.
• Sentiment analysis using Naïve Bayes to identify potential malicious workers.
• Introduces the use of referrals to alleviate new workers’ cold start problem.
• Results show that our approach achieves greater accuracy in task allocation.
摘要
•A framework computes workers trustworthiness based on trust and reputation factors.•It produces a degree of trustworthiness score for a fairer decision.•Sentiment analysis using Naïve Bayes to identify potential malicious workers.•Introduces the use of referrals to alleviate new workers’ cold start problem.•Results show that our approach achieves greater accuracy in task allocation.
论文关键词：Spatial Crowdsourcing,Multi-criteria factor,Trust and reputation system,Fuzzy inference system,Trustworthiness evaluation,Sentiment analysis
论文评审过程：Received 7 October 2021, Revised 5 August 2022, Accepted 13 August 2022, Available online 20 August 2022, Version of Record 27 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118592
