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Improving intelligent analytics through guidance: analysis and refinement of patterns of use and recommendation methods for data mining and analytics systems

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dc.contributorAtkison, Travis Levestis
dc.contributorBrown, David B.
dc.contributorSmith, Randy K.
dc.contributorParrish, Allen Scott
dc.contributor.advisorDixon, Brandon
dc.contributor.authorPate, Jeremy
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2019-08-01T14:23:51Z
dc.date.available2019-08-01T14:23:51Z
dc.date.issued2019
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractIn conjunction with the proliferation of data collection applications, systems that provide functionality to analyze and mine this resource also increase in count and complexity. As a part of this growth, understanding how users navigate these systems, and how that navigation influences the resulting extracted information and subsequent decisions becomes a critical component of their design. A central theme of improving the understanding of user behavior and tools for their support within these systems focuses the effort to gain a context-aware view of analytics system optimization. Through distinct, but interwoven, articles this research examines the specific characteristics of usage patterns of a specific example of these types of systems, construction of and educational support system for new and existing users, and a decision-tree supported workflow optimization recommender system. These components combine to yield a method for guided intelligent analytics that uses behavior, system knowledge, and workflow optimization to improve the user experience and promote efficiency of use for systems of this type.en_US
dc.format.extent114 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0003294
dc.identifier.otherPate_alatus_0004D_13838
dc.identifier.urihttp://ir.ua.edu/handle/123456789/6107
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectComputer science
dc.titleImproving intelligent analytics through guidance: analysis and refinement of patterns of use and recommendation methods for data mining and analytics systemsen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Computer Science
etdms.degree.disciplineComputer Science
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.

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