Online multi-task collaborative filtering for on-the-fly recommender systems

• Main Authors: WANG, Jialei, HOI, Steven C. H., ZHAO, Peilin, LIU, Zhi-Yong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Recommender systems; Collaborative Filtering; Online learning; Multi-task Learning; Computer Sciences; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/2334; https://ink.library.smu.edu.sg/context/sis_research/article/3334/viewcontent/Online_Multi_Task_Collaborative_Filtering_for_On_the_Fly_Recommender_Systems.pdf
• Institution: Singapore Management University

Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training...