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Classification and modeling of the quality of contextual information

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dc.contributor.author Razzaque, Mohammed Abhur
dc.contributor.author Dobson, Simon
dc.contributor.author Nixon, Paddy
dc.date.accessioned 2011-10-26T16:07:42Z
dc.date.available 2011-10-26T16:07:42Z
dc.date.issued 2007
dc.identifier.uri http://hdl.handle.net/10344/1524
dc.description peer-reviewed en_US
dc.description.abstract Pervasive and autonomic environments make extensive use of contextual information to guide adaptations to changing external demands and circumstances. Context takes many forms, and some form of categorisation of information from different viewpoints can assist designers in deciding how information should affect behaviour, and inform the handling of uncertain or conflicting information. We discuss the various approaches to context modeling, and derive an initial methodology for including contextual information in adaptive applications. en_US
dc.language.iso eng en_US
dc.publisher IEEE Computer Society en_US
dc.relation.ispartofseries IEEE TCAAS Letters;
dc.rights ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE en_US
dc.subject pervasive computing en_US
dc.subject autonomic computing en_US
dc.subject developmental methodologies en_US
dc.title Classification and modeling of the quality of contextual information en_US
dc.type Article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.type.restriction none en
dc.contributor.sponsor SFI
dc.relation.projectid grant under Secure and Predictable Pervasive Computing


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