Mapping from student domain into website category

  • Authors:
  • Xiaosong Li

  • Affiliations:
  • Department of Computing and IT, Unitec Institute of Technology, Auckland, New Zealand

  • Venue:
  • ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
  • Year:
  • 2011

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Abstract

The existing e-learning environments focus on the reusability of learning resources not adaptable to suit learners' needs [1]. Previous research shows that users' personalities have impact on their Internet behaviours and preferences. This study investigates the relationship between user attributes and their website preferences by using a practical case which suggested that there seemed to be relationships between a student's gender, age, mark and the type of the website he/she has chosen aiming to identify valuable information which can be utilised to provide adaptive e-learning environment for each student. This study builds ontology taxonomy in the student domain first, and then builds ontology taxonomy in the website category domain. Mapping probabilities are defined and used to generate the similarity measures between the two domains. This study uses two data sets. The second data set was used to learn similarity measures and the first data set was used to test the similarity formula. The scope of this study is not limited to e-learning system. The similar approach may be used to identify potential sources of Internet security issues.