Enhancing ontology-based context modeling with temporal vector space for ubiquitous intelligence

Shermann S.M. Chan, Qun Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Context is the information, which is created and obtained from the surrounding environment for the interaction between humans and computational services. A generic model is a key accessor to the context in any context-aware applications for ubiquitous computing. In the past decades, a number of context modeling techniques have been proposed e.g. markup scheme based, logic-based, graphical, and ontology-based. Since ontology in its nature is a promising tool to specify concepts and interrelations, it has been widely adopted in context modeling. However, in the rapid changing environments, semantics may vary according to the time factors and dynamic group of users. In this paper, we propose an ontology-based context model with temporal vector space in order to complement this deficiency.

Original languageEnglish
Title of host publicationProceedings - 20th International Conference on Advanced Information Networking and Applications
Pages669-674
Number of pages6
DOIs
Publication statusPublished - 2006 Nov 22
Event20th International Conference on Advanced Information Networking and Applications - Vienna, Austria
Duration: 2006 Apr 182006 Apr 20

Publication series

NameProceedings - International Conference on Advanced Information Networking and Applications, AINA
Volume1
ISSN (Print)1550-445X

Conference

Conference20th International Conference on Advanced Information Networking and Applications
CountryAustria
CityVienna
Period06/4/1806/4/20

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Chan, S. S. M., & Jin, Q. (2006). Enhancing ontology-based context modeling with temporal vector space for ubiquitous intelligence. In Proceedings - 20th International Conference on Advanced Information Networking and Applications (pp. 669-674). [1620265] (Proceedings - International Conference on Advanced Information Networking and Applications, AINA; Vol. 1). https://doi.org/10.1109/AINA.2006.171