PCCF: Periodic and continual temporal co-factorization for recommender systems

• Main Authors: GUO, Guibing, ZHU, Feida, QU, Shilin, WANG, Xingwei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Continual effect; Periodic effect; Rating timestamps; Recommender systems; Temporal model; Co-factorization model; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4860; https://ink.library.smu.edu.sg/context/sis_research/article/5863/viewcontent/PCCF_av.pdf
• Institution: Singapore Management University

Rating-only collaborative filtering has been extensively studied for decades with great improvements achieved in predicting a user’s preference on a target item at a particular time point. Yet, it remains a research challenge on how to capture users’ rating patterns which may drift over time. In thi...