An analysis of collaborative filtering datasets

dc.check.embargoformatNot applicableen
dc.check.infoNo embargo requireden
dc.check.opt-outNoen
dc.check.reasonNo embargo requireden
dc.check.typeNo Embargo Required
dc.contributor.advisorSorensen, Humphreyen
dc.contributor.authorGriffith, Josephine
dc.contributor.funderNational University of Ireland, Galwayen
dc.date.accessioned2018-02-21T13:14:55Z
dc.date.available2018-02-21T13:14:55Z
dc.date.issued2018
dc.date.submitted2018
dc.description.abstractThe work described in this thesis pertains to the area of Collaborative Filtering and focuses on collaborative filtering datasets and specially-defined portions of the datasets called views. The high level goal of the work is to better understand how different characteristics of datasets affects the performance of collaborative filtering techniques. Datasets, and views, are compared across a number of different experiments: some relating to techniques and accuracy and others relating to ideas of performance prediction.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationGriffith, J. 2018. An analysis of collaborative filtering datasets. PhD Thesis, University College Cork.en
dc.identifier.endpage186en
dc.identifier.urihttps://hdl.handle.net/10468/5532
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2018, Josephine Griffith.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectCollaborative filteringen
dc.subjectDataset viewsen
dc.subjectPerformance predictionen
dc.subjectMachine learningen
dc.thesis.opt-outfalse
dc.titleAn analysis of collaborative filtering datasetsen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD (Science)en
ucc.workflow.supervisorh.sorensen@ucc.ie
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
JosephineGriffith.pdf
Size:
1.62 MB
Format:
Adobe Portable Document Format
Description:
Full Text E-thesis
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
5.62 KB
Format:
Item-specific license agreed upon to submission
Description: