Context Modelling Using Semantic Web Technologies

Hyosook Jung
Department of Computer Science Education
Korea University, Seoul, KOREA

Sujin Yoo
Department of Computer Science Education
Korea University, Seoul, KOREA

Seongbin Park
Department of Computer Science Education
Korea University, Seoul, KOREA

Abstract:

In this paper, we propose an ontology-based context model that generically describes different contexts surrounding each user. By using ontology, it can categorize all contexts and find contextual information from relations between contexts so that it can offer adaptive services according to user’s context. A user can write a context rule using a context description language that we propose and our system compiles the context rules and find relevant information. We demonstrate how our system can be used using examples from popular social network services.

Keywords:

Context modelling, semantic web.

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CITE THIS PAPER AS:
Hyosook JUNG, Sujin YOO, Seongbin PARK, Context Modelling Using Semantic Web Technologies, Studies in Informatics and Control, ISSN 1220-1766, vol. 21 (2), pp. 173-180, 2012. https://doi.org/10.24846/v21i2y201207

1. Introduction

With the development of context-aware computing, different approaches have been proposed for providing services suited to a particular person. Context refers to any information that can be used to characterize the user’s current situation such as time, place, device, task, etc. One of the most important things for context-awareness applications is context modeling because a well-designed context model can support expressing and analyzing the context. Early applications addressed a specific context model for just one application, but recently they are interested in generic context models that facilitate context sharing and reusing, or interoperability between different applications.

In this paper, we propose a generic context model based on ontologies [1] that specify concepts and relations between the concepts about the context. The ontologies can represent the context as structured data that computers can understand, and makes it easy to combine, share, or reuse the contextual information. We first define a context ontology written in Web Ontology Language (OWL) [2] for building the vocabulary to describe context. Then, we represent the contextual information written in Resource Description Framework (RDF) [3] using the context ontology. Our system can not only express the context meaningfully, but reason new contextual information from existing contextual information. We also develop a context rule that allows users to represent the contextual information and define what they want a system to do.

The context rule consists of conditions and actions and is written using a context description language. A context compiler compiles the context rule, analyzes contextual information and provides a suitable content or services. Each context is represented by a 4-tuple structure (<ContextType>, <Subject>, <Verb>, <Object>) and can be combined using operations. The action defines what kind of content or service is offered. The context rule can be dynamically modified according to user’s need and provide the services specialized to each user.

This paper is structured as follows. Section 2 describes related works to our research. Section 3 explains our approach to model contexts. The system architecture that we propose is described in section 4. Section 5 describes scenarios of how our system can be used. Section 6 concludes the paper.

References:

ANTONIOU, G., F. van HARMELEN, A Semantic Web Primer, The MIT Press, 2004.
OWL, http://www.w3.org/TR/owl-features/
RDF, http:// www.w3.org/RDF/
McGUINNESS, D. L., F. van HARMELEN, OWL Web Ontology Language Overview W3C Recommendation, http://www.w3.org/TR/owl-features, 2004.
HEFLIN, J., R. VOLZ, J. DALE, Web Ontology Requirements, Proposed W3C Working Draft, http://km.aifb.uni-karlsruhe.de/projects/owl/index.html, 2002.
WANG, X. H., D. Q. ZHANG, T. GU, H. K. PUNG, Ontology based Context Modelling and Reasoning using OWL, Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004, pp. 18-22.
RANGANATHAN, A., R. H. CAMPBELL, A. RAVI, A. MAHAJAN, ConChat: A Context-aware Chat Program, Pervasive Computing, 2002, vol. 1, no. 3, pp. 51-57.
CERQUEIRA, R., C. K., HESS, M. ROM&AACUTE;N, R. H. CAMPBELL, Gaia: A Development Infrastructure for Active Spaces, Workshop on Application Models and Programming Tools for Ubiquitous Computing, 2001.
JUNG, H., J. AHN, H. KIM, S. PARK, Contextual Information in Smart Home, International Workshop on Ubiquitous Web Applications, 2008.
WU, H., G. HOUBEN, P. De BRA, AHAM: A Reference Model to Support Adaptive Hypermedia Authoring, Proceedings of the Conference on Information Science, 1998, pp. 51-76.
GOH, E., D. CHIENG, A. K. MUSTAPHA, Y. C. NGEOW, H.-K. LOW, A Context-Aware Architecture for Smart space Environment, Proceedings of the 7th International Conference on Multimedia and Ubiquitous Engineering, 2007, pp. 908-913.
RACK, C., S. ARBANOWSKI, S. STEGLICH, Context-aware, Ontology-based Recommendations, International Symposium on Applications and the Internet Workshops, 2006, pp. 23-27.
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