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dc.contributor.authorPereira, Mateus Malvessi
dc.date.accessioned2020-04-08T13:09:04Z
dc.date.available2020-04-08T13:09:04Z
dc.identifier.urihttp://hdl.handle.net/10222/78415
dc.description.abstractMany algorithms in the Information Retrieval domain have been developed considering training models using vast amounts of data. The acquisition of this data, however, is time-consuming and requires lots of human effort. Active Learning techniques try to solve this problem by reducing the number of instances needed in the training phase by selecting relevant instances to be labelled. Although such an approach has been proved to be effective, it is still hard to understand how the model is changing after every relevance feedback. As a potential solution, the use of visualizations to help users to understand models is becoming a widespread approach both to understand the overall behaviour of a model and to analyze individual data instances. In this thesis, I explore the utilization of a Learning to Rank algorithm in a relevance feedback scenario and the use of visualizations to understand the reasoning behind the model's ranking decisions.en_US
dc.language.isoenen_US
dc.subjectInformation Retrievalen_US
dc.subjectMachine Learningen_US
dc.subjectMachine Learning Interpretationen_US
dc.subjectVisualizationen_US
dc.subjectRelevance Feedbacken_US
dc.subjectLearning to Ranken_US
dc.subjectVisual Analyticsen_US
dc.subjectExplainable Artificial Inteligenceen_US
dc.titleInteractive Learning To Rank And Visual Rank Interpretationen_US
dc.date.defence2020-03-25
dc.contributor.departmentFaculty of Computer Scienceen_US
dc.contributor.degreeMaster of Computer Scienceen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorDr. Michael McAllisteren_US
dc.contributor.thesis-readerDr. Evangelos Miliosen_US
dc.contributor.thesis-readerDr. Derek Reillyen_US
dc.contributor.thesis-supervisorDr. Fernando Paulovichen_US
dc.contributor.thesis-supervisorDr. Elham Etemaden_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.copyright-releaseYesen_US
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