Intelligent techniques for recommender systems
Contribuinte(s) |
Zhou, Wanlei Li, Gang |
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Data(s) |
01/07/2013
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Resumo |
This thesis focuses on the data sparsity issue and the temporal dynamic issue in the context of collaborative filtering, and addresses them with imputation techniques, low-rank subspace techniques and optimizations techniques from the machine learning perspective. A comprehensive survey on the development of collaborative filtering techniques is also included. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Deakin University, Faculty of Science, Engineering and Built Environment, School of Information Technology |
Relação |
http://dro.deakin.edu.au/eserv/DU:30062528/ren-agreement-2013.pdf http://dro.deakin.edu.au/eserv/DU:30062528/ren-intelligenttechniques-2013A.pdf |
Direitos |
The Author. All Rights Reserved |
Palavras-Chave | #Recommender systems #Collaborative filtering #Imputation techniques #Low-rank subspace techniques #Optimizations techniques #Rating pattern subspace |
Tipo |
Thesis |