A geo-location context-aware mobile learning system with adaptive correlation computing methods

Nagato Kasaki, Shuichi Kurabayashi, Yasushi Kiyoki

Research output: Contribution to journalConference articlepeer-review

9 Citations (Scopus)


This paper proposes a context-aware mobile learning system with adaptive correlation computing methods. This system enables users to enhance their knowledge by correlating it with daily experiences. The proposed system contains a hybrid metric vector space to define the correlation between heterogeneous metadata vectors of the user context and learning material. The system integrates heterogeneous metric vector spaces with definitions of the semantic relations between the vector spaces. The significant feature of this system is a hybrid adaptation mechanism for the calculation of correlation. The adaptation mechanism has multidirectional adaptation functions for various learning materials, situations, and learners. We propose a revise-localize-personalize (RLP) adaptation model. In the adaptation mechanism, users only have to improve the metadata or the relations just in their relevant field. The advantage of the system is that the system reduces the time-intensive efforts required for describing direct relations between user contexts and learning materials. This paper presents the feasibility of the context-aware heterogeneous information provision with the hybrid metric vector space, by implementing an actual mobile application system and examining real-world experiments on data provision.

Original languageEnglish
Pages (from-to)593-600
Number of pages8
JournalProcedia Computer Science
Publication statusPublished - 2012
Externally publishedYes
Event3rd International Conference on Ambient Systems, Networks and Technologies, ANT 2012 and 9th International Conference on Mobile Web Information Systems, MobiWIS 2012 - Niagara Falls, ON, Canada
Duration: 2012 Aug 272012 Aug 29


  • Adaptive computing
  • Context-aware
  • Correlation computing
  • Mobile learning

ASJC Scopus subject areas

  • Computer Science(all)


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