User Model Clustering

• 作者: Loc Nguyen
• 来源期刊: 数据分析和信息处理(英文)
• 学科: 医学
• 关键词: USER MODEL CLUSTER
• 年，卷（期）: sjfxhxxclyw,（2）
• 页码范围: 41-48
• 页数: 8页
• 分类号: R73

摘要

User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network.