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Nguyen, L. and Phung, D. (2009) Combination of Bayesian Network and Overlay Model in User Modeling. Proceedings of 4th International Conference on Interactive Mobile and Computer Aided Learning (IMCL 2009), 22-24 April 2009, Amman.

has been cited by the following article:

• TITLE: User Model Clustering

  AUTHORS: Loc Nguyen

  KEYWORDS: User Model, Cluster

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.2 No.2, May 28, 2014

  ABSTRACT: 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.