DYNAMIC ONTOLOGIES THAT ENCODE AND MANAGE RELEVANCE IN CONTEXT AWARE SYSTEMS

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dc.contributor.advisorAgrawala, Ashoken_US
dc.contributor.authorGramsky, Nicholasen_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2019-02-08T06:33:20Z
dc.date.available2019-02-08T06:33:20Z
dc.date.issued2018en_US
dc.description.abstractContext aware systems, to date, tend to fall into one of two categories: domain specific or generic across multiple domains. Domain specific systems are single-use instances – that is, establishing the ability to manage context for an additional domain necessitates the creation of an additional system. Authors of such systems should instead strive for generic ones. Generic context management systems require a generic modeling and context delivery system. Previous research has shown that generic context aware systems prove to be quite dynamic through their use of ontologies. These ontologies, however, are very rigid in nature, requiring additional software to mature and manage instantiated models, filter relevant information, or pre-cache information. The result is users who wish to use generic systems must encode relevance across ontological models, filters, and newly created external software with each re-use in order to manage context manipulation at run time. Through the design and implementation of Rover3, while leveraging the concept of an Automatic and Dynamic Information Model (ADIM) methodology, we outline what we believe how context aware systems should function. By providing a framework to encode relevance within ontologies, we minimize the way to present and consume relevant information. Our context management framework uses dynamic ontologies to deliver relevant information to users striving to achieve goals for any given situation. Walking through an accident response case study we showcase the aforementioned features of Rover3, showing how such incidents can benefit from context aware systems. The value of Rover3 is expressed through an extensibility study where efforts to expand existing ontological models are compared between Rover2 and Rover3. This dissertation presents: • The notion of relevant context and how it can be managed at runtime through a generic context aware system. • The required primitives and rules for modeling any generic situation. • The Automatic and Dynamic Information Model (ADIM) methodology, how one can encode relevance in a general information model, and exhaustive grammar and rules for this version of ADIM. • The Rover3 system and its application of ADIM, showcasing how it provides a generic framework to model and manage context that does not require any additional software.en_US
dc.identifierhttps://doi.org/10.13016/d6wt-sozk
dc.identifier.urihttp://hdl.handle.net/1903/21752
dc.language.isoenen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.titleDYNAMIC ONTOLOGIES THAT ENCODE AND MANAGE RELEVANCE IN CONTEXT AWARE SYSTEMSen_US
dc.typeDissertationen_US

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