论文标题
决策中的分布式语言表示：分类法，关键要素和应用以及数据科学和可解释的人工智能的挑战
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
论文作者
论文摘要
分布式语言表示是在语言决策中建模偏好信息的不确定性和复杂性的强大工具。为了提供有关决策中分布式语言表征发展的全面观点，我们介绍了现有的分布式语言表征的分类法。然后，我们回顾了决策中分布式语言信息处理的关键要素，包括距离测量，聚合方法，分布式语言偏好关系以及分布式语言多元属性决策模型。接下来，我们从数据科学和可解释的人工智能的角度就正在进行的挑战和未来的研究方向进行了讨论。
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.
