A Hybrid Semantic Integration Framework for Improving Data Quality

dc.Location2017 T 58.5 H36
dc.SupervisorProfessor Khaled Shaalan
dc.contributor.authorHamdy, Mahmoud Esmat
dc.date.accessioned2018-06-06T10:35:20Z
dc.date.available2018-06-06T10:35:20Z
dc.date.issued2017-11
dc.description.abstractThis study aims to develop a new hybrid framework of semantic integration to improve data quality in order to resolve the problem from scattered data sources and rapid expansions of data. The proposed framework is based on a solid background that is inspired by previous studies. Significant and seminal research articles are reviewed based on selection criteria. A critical review is conducted in order to determine a set of qualified semantic technologies that can be used construct a hybrid semantic integration framework. The proposed framework consists of six layers and one component as follows: Source layer, Translation Layer, XML layer, RDF layer, Inference Layer, application layer and ontology component. The proposed framework face two challenges and one conflict, we fix it while compose the framework. The proposed framework examined to improve data quality for four dimensions of data quality dimensions.en_US
dc.identifier.other2013110154
dc.identifier.urihttp://bspace.buid.ac.ae/handle/1234/1143
dc.language.isoenen_US
dc.publisherThe British University in Dubaien_US
dc.subjectimproving data qualityen_US
dc.subjecthybrid frameworken_US
dc.subjectsemantic integrationen_US
dc.subjectsemantic technologiesen_US
dc.titleA Hybrid Semantic Integration Framework for Improving Data Qualityen_US
dc.typeDissertationen_US
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