dc.contributor.authorYap, Ghim Eng
dc.date.accessioned2010-08-06T03:50:10Z
dc.date.accessioned2017-07-23T08:29:07Z
dc.date.available2010-08-06T03:50:10Z
dc.date.available2017-07-23T08:29:07Z
dc.date.copyright2008en_US
dc.date.issued2008
dc.identifier.citationYap, G. E. (2008). Learning and exploiting context dependencies for robust recommendations. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/41737
dc.description.abstractWe consider the recommendation problem, where a set of available items or choices are rated and recommended to users accordingly. Over and above the ratings information used in traditional filtering algorithms, the context of the user-recommender interaction is used to improve the recommendation quality. Specifically, we study how the effective learning and exploitation of context dependencies can help to generate more personal and relevant recommendations.en_US
dc.format.extent174 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Information systems::Information systems applicationsen_US
dc.titleLearning and exploiting context dependencies for robust recommendationsen_US
dc.typeThesis
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.contributor.supervisorPang Hwee Hwa
dc.contributor.supervisorTan Ah Hweeen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (SCE)en_US
dc.identifier.doihttps://doi.org/10.32657/10356/41737


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