Joint Optimization of Tree-based Index and Deep Model for Recommender Systems

Understand

Large-scale industrial recommender systems are usually confronted with computational problems due to the enormous corpus size.

• To retrieve and recommend the most relevant items to users under response time limits, resorting to an efficient index structure is an effective and practical solution.
• The previous work Tree-based Deep Model (TDM) \cite{zhu2018learning} greatly improves recommendation accuracy using tree index.
• By indexing items in a tree hierarchy and training a user-node preference prediction model satisfying a max-heap like property in the tree, TDM provides logarithmic computational complexity w.r.t.