A new preference classification approach: The λ-dissensus cluster algorithm
提出一种融合社会选择理论和决策理论的偏好聚类算法，利用序向量表示偏好，并通过内部验证和真实数据实验展示其有效性。
Preferences and their classification are essential in many decision making processes. However, grouping preferences is not an easy matter because their very nature. In this paper a new preference clustering algorithm is proposed that incorporates the key features of preferences, usually represented by order vectors, and it takes ideas from Social Choice Theory, Decision Making Theory and Cluster Analysis as sources of inspiration. Additionally, a study of the main properties of our proposal is included as well as several internal validation measurements. Finally and in order to improve understanding of the proposed approach, assorted experiments on real data are included.