Volume 7 Number 1 (Jan. 2012)
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JSW 2012 Vol.7(1): 176-185 ISSN: 1796-217X
doi: 10.4304/jsw.7.1.176-185

Content Adaptation For Context-Aware Service

Jui-Fa Chen, Ying-Hong Wang, Jingo Chenghorng Liao, and Chen-An Wang
Department of Computer Science and Information Engineering, Tamkang University, New Taipei City, Taiwan

Abstract—The current and developing trend for consumers is to access web contents and applications anytime, anywhere, and on any devices. Most of Internet services and most of web contents have been designed for desktop computers, and often contain rich medias, such as images, audios, and videos. However, some devices are different from network connectivity, processing power, storage capacity, display size, and formative handling capability. In many cases, the content designed for computers is not suitable for new (and often mobile) devices. Therefore, content adaptation is needed in order to optimize the service for different devices and access methods. This research discusses the context issues for web content adaptation. The CC/PP and UAProf are two related standards that define the format to describe the capabilities of devices for accessing content. A context-aware environment should allow adaptive access to context information. In this paper, first we proposed an inference mechanism for context-aware service. Through this inference mechanism, users using different devices can get appropriate contents based on inference results. Second, we can demonstrate the correlation between classes and individuals, and provide better scalability by means of building ontologies. Lastly, SWRL depends on ontology based rule languages. Rules written based on SWRL can directly use an established object relationship from ontology.

Index Terms—Context-Aware, Adaptation, SWRL, Inference, UAprof, Web Services.

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Cite:Jui-Fa Chen, Ying-Hong Wang, Jingo Chenghorng Liao, and Chen-An Wang, "Content Adaptation For Context-Aware Service," Journal of Software vol. 7, no.1, pp. 176-185, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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