论文标题
异常意识的多人评估系统，并改善了模糊加权
Abnormal-aware Multi-person Evaluation System with Improved Fuzzy Weighting
论文作者
论文摘要
存在一种现象，即主观性高度在于日常评估过程。我们的研究主要集中于具有异常检测的多人评估系统，以最大程度地减少主观评估带来的可能性不准确。我们选择了两阶段筛选方法，该方法包括粗糙的筛选和得分加权的Kendall-$τ$距离，以获取异常数据，再加上假设测试，以缩小全球差异。然后，我们使用模糊综合评估方法（FSE）来确定审阅者给出的分数及其可靠性的重要性，并在最终结论中为每个审阅者更加公正地重量。结果表明，明确而全面的排名，而不是单方面得分，我们在滤除异常数据以及合理客观的重量确定机制方面有效率。我们可以感觉到，通过我们的研究，人们将有机会修改多人评估系统，以达到公平和相对更高的竞争氛围。
There exists a phenomenon that subjectivity highly lies in the daily evaluation process. Our research primarily concentrates on a multi-person evaluation system with anomaly detection to minimize the possible inaccuracy that subjective assessment brings. We choose the two-stage screening method, which consists of rough screening and score-weighted Kendall-$τ$ Distance to winnow out abnormal data, coupled with hypothesis testing to narrow global discrepancy. Then we use Fuzzy Synthetic Evaluation Method(FSE) to determine the significance of scores given by reviewers as well as their reliability, culminating in a more impartial weight for each reviewer in the final conclusion. The results demonstrate a clear and comprehensive ranking instead of unilateral scores, and we get to have an efficiency in filtering out abnormal data as well as a reasonably objective weight determination mechanism. We can sense that through our study, people will have a chance of modifying a multi-person evaluation system to attain both equity and a relatively superior competitive atmosphere.
