Titlebook: Recommender Systems; Frontiers and Practi Dongsheng Li,Jianxun Lian,Xing Xie Book 2024 Publishing House of Electronics Industry 2024 recomm

六邊形

抵制

https://doi.org/10.1007/978-981-99-8964-5recommender systems; recommendation algorithm; data mining; Recommender System Frontiers; Recommender Sy

學術討論會

GAVEL

synovial-joint

figure

玩忽職守

憤怒事實

Practical Recommender System,plications based on the code in the Microsoft Recommenders repository and a cloud-based reference architecture. Readers are encouraged to follow the steps and methods in the text in a hands-on manner and experiment using the algorithms introduced in previous chapters.

Abominate

的’

Deep Learning-Based Recommendation Algorithms,algorithms are optimized for specific problems, and there are often limitations in practical applications. Therefore, at the system design level, algorithm integration or fusion needs to be considered.