Big data management and mining models and their applications

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dc.contributor.authorOlawoyin, Anifat
dc.contributor.examiningcommitteeWang, Yang (Computer Science)
dc.contributor.examiningcommitteeHo, Carl Ngai Man (Electrical and Computer Engineering)
dc.contributor.examiningcommitteeEzeife, Christiana Ijeoma (University of Windsor)
dc.contributor.supervisorLeung, Carson
dc.date.accessioned2024-07-31T18:35:54Z
dc.date.available2024-07-31T18:35:54Z
dc.date.issued2024-07-02
dc.date.submitted2024-07-22T00:44:45Zen_US
dc.degree.disciplineComputer Science
dc.degree.levelDoctor of Philosophy (Ph.D.)
dc.description.abstractThe world is dynamic, so are big data. The evolving challenges of managing big data volume, variety, veracity, validity, and velocity has resulted in several studies focusing on solving one or more of these perplexing issues. In this Ph.D. research, I focus on the evolving issues arising from big data variety, veracity, privacy, and accessibility. First, I design a conceptual model for capturing and storing variety of big data types including structured, semi-structured and unstructured data types and in addition, design a metadata collection framework for managing the big data in support of machine learning and open data FAIR principle of Findable, Accessibility, Interoperability and Re-usability such that the information about the data are available beyond the life cycle of the data. Second, I design hierarchical spatial-temporal model (HSTM) for managing individual record in big data in the aforementioned open data lake architecture with metadata collection framework. Third, I extend the HSTM and design the resulting hierarchical spatial-temporal privacy preserving model (HSTPPM) for preserving privacy of individual record in big data. Fourth, I extend and design applications of the HSTPPM to big data co-occurrence pattern mining and big data visualization.
dc.description.noteOctober 2024
dc.description.sponsorshipMitacs: http://dx.doi.org/10.13039/501100004489 NSERC: https://doi.org/10.13039/501100000038
dc.identifier.urihttp://hdl.handle.net/1993/38346
dc.language.isoeng
dc.subjectdata science
dc.subjectbig data
dc.subjectdata mining
dc.subjectdata model
dc.subjecthierarchical model
dc.subjecthierarchical spatiotemporal model
dc.subjectprivacy preserving model
dc.subjectfrequent pattern mining
dc.subjectdata visualization
dc.subjectdata management
dc.subjectcooccurrence pattern mining
dc.titleBig data management and mining models and their applications
local.subject.manitobano
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