When using several possible linguistic terms with different weights (represented by probability values) to express preferences, the probability distribution of those linguistic terms is usually hard to be obtained. In this paper, we utilize degree values to reflect the weights of possible linguistic terms and first propose a novel concept called degree-based linguistic term set (DLTS) from the perspective of degree. Then we present a new multi-attribute three-way decision method under the environment of DLTSs. Furthermore, considering that if only one person is involved in decision-making process, it may produce unreasonable or unfair evaluation results. We choose multiple decision-makers to participate in the decision-making process, and propose a multi-attribute group three-way decision method by utilizing the idea of TOPSIS method under the environment of DLTSs. Since the weights of multiple decision-makers (DMs) may be different, we give a method to determine the weights by using the idea of information gain based on the three-way decision results of each decision-maker (DM). Finally, we compare our decision method with an existing decision method, and illustrate the effectiveness of our method through a concrete example.

当使用多个不同权重（用概率值表示）的可能的语言术语来表达偏好时，通常很难获得这些语言术语的概率分布。在本文中，我们利用度值来反映可能的语言术语的权重，并首先从度的角度提出了一个称为基于度的语言术语集（DLTS）的新概念。然后我们提出了一种新的DLTS环境下的多属性三向决策方法。此外，考虑到如果只有一个人参与决策过程，可能会产生不合理或不公平的评价结果​​。我们选择多个决策者参与决策过程，并在DLTSs环境下，利用TOPSIS方法的思想，提出了一种多属性群三向决策方法。由于多个决策者（DM）的权重可能不同，我们给出了一种基于每个决策者（DM）的三向决策结果，利用信息增益的思想来确定权重的方法。最后，我们将我们的决策方法与现有的决策方法进行比较，并通过一个具体的例子说明我们的方法的有效性。