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Relative preference-based recommender systems

Liu, Shaowu 2016, Relative preference-based recommender systems, PhD. thesis, School of Information Technology, Deakin University.

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Title Relative preference-based recommender systems
Author Liu, Shaowu
Institution Deakin University
School School of Information Technology
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name PhD.
Thesis advisor Li GangORCID iD for Li Gang orcid.org/0000-0003-1583-641X
Beliakov GlebORCID iD for Beliakov Gleb orcid.org/0000-0002-9841-5292
Xiong, Ping
Date submitted 2016-06
Keyword(s) Computing
Preference Relation
Data sets
Data manipulation
Web 2.0
Summary This study investigates the problem of making recommendations to users, such as recommending a movie. Several novel models are proposed to make accurate recommendations by analyzing both the explicit and implicit data. Experiment results have confirmed improvements over state-of-the-art models.
Language eng
Field of Research 080699 - Information Systems not elsewhere classified 100%
Socio Economic Objective 970108 - Expanding Knowledge in the Information and Computing Sciences 100%
Description of original xiv, 138 pages : tables, figures, some coloured
Copyright notice ©The Author. All Rights Reserved
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30088962

Document type: Thesis
Collections: Higher degree theses (Open Access)
Open Access Collection
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Created: Wed, 16 Nov 2016, 10:50:14 EST by Deb Gray

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.