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Mapping features to context Information: supporting context variability for context-aware pervasive applications.

Jaroucheh, Zakwan, Liu, Xiaodong and Smith, Sally (2010) Mapping features to context Information: supporting context variability for context-aware pervasive applications. In: Proceedings of IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technologies (WI-IAT 2010). IEEE Computer Society, Toronto, Canada, pp. 611-614. ISBN 978-1-4244-8482-9

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Abstract/Description

Context-aware computing is widely accepted as a promising paradigm to enable seamless computing. Several middlewares and ontology-based models for describing context information have been developed in order to support context-aware applications. However, the context variability, which refers to the possibility to infer or interpret different context information from different perspectives, has been neglected in the existing context modeling approaches. This paper presents an approach for context-aware software development based on a flexible product line based context model which significantly enhances reusability of context information by providing context variability constructs to satisfy different application needs.

Item Type: Book Section
ISBN: 978-1-4244-8482-9
Electronic ISBN: 978-0-7695-4191-4
Additional Information: “© © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
Uncontrolled Keywords: context-awareness; context variability; feature model; software product model; pervasive applications;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3900
Depositing User: Computing Research
Date Deposited: 03 Feb 2011 16:03
Last Modified: 19 Nov 2013 13:43
URI: http://researchrepository.napier.ac.uk/id/eprint/3900

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