Incremental Factorization Machines for Persistently Cold-starting Online Item Recommendation


Real-world item recommenders commonly suffer from a persistent cold-start problem which is caused by dynamically changing users and items. In order to overcome the problem, several context-aware recommendation techniques have been recently proposed. In terms of both feasibility and performance, factorization machine (FM) is one of the most promising methods… (More)


8 Figures and Tables

Slides referencing similar topics