广义区间梯形模糊软集在群偏好集结中的应用

针对群推荐中个体偏好信息如何集成群体偏好信息,不同用户对商品关注的属性不完全相同,以及用户对商品属性权重分配不同的复杂问题,提出区间梯形模糊软集的群偏好集结模型。首先,结合广义区间梯形模糊集和软集的概念建立广义区间梯形模糊软集的概念,定义其基本运算性质；其次,将模糊语言映射成广义区间梯形模糊数,利用广义区间梯形模糊软集的并、交运算,以及广义区间梯形模糊数的重心算法进行排序,将个体用户的偏好信息集结成群偏好信息；最后,以汽车的推荐为例介绍群偏好集结算法。算例结果显示,用该模型解决群体偏好集结是合理和有效的。

Generalized interval-valued trapezoidal fuzzy soft set and its application in group preferences aggregation

Owing to that different users focus on attributes of the same item is not exactly the same, individuals' weight distribution for goods attributes are not the same. A method of the generalized interval-valued trapezoidal fuzzy soft set was proposed to deal with this kind of recommendation problems. First, the concept of generalized interval-valued trapezoidal fuzzy soft set was established by combining the concepts of generalized interval-valued trapezoidal fuzzy set and soft set, some basic operations on a generalized interval-valued trapezoidal fuzzy soft set were defined, such as “and” operation, and “or” operation. Using these operations, as well as the center of gravity method of the generalized interval-valued trapezoidal fuzzy numbers, commodities could be ranked. A group preference model from the preferences of the group members could be constructed. Finally, this paper used the car recommendation as an example to introduce the group preference aggregation algorithm and this numerical example was given to illustrate the feasibility and effectiveness of the proposed method.