前言
1. 本次整理方式为时间线的形式，未来可能从其他视角和维度进行整理。
2. 由于本人知识有限，对于未出现在下文的推荐模型并不代表不经典，欢迎大家补充。
3. 文中提及的模型都标有对应参考文献，具体细节可阅读论文原文。
4. 整理此文的目的是给大家一个清晰的脉络，可当作一篇小小综述。从信息过载概念的提出到推荐系统的起源，从前深度学习时代的推荐系统到劲头正热的深度推荐系统，再到最后对于深度学习技术带来的推荐系统性能提升的质疑，每个阶段都是必不可少的。
5. 希望推荐系统领域未来仍然可以在曲折中前进。
结尾
1. 回看推荐发展的30年，尽管前进的路上有过批评、有过怀疑，但一直在进步。
2. 至于推荐系统未来的发展何去何从，需要我们每个当前参与的人一起努力。
3. 也希望后人再总结的时候发现推荐系统在大方向上一直在茁壮成长。
参考文献
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以上文献均可在https://github.com/hongleizhang/RSPapers中找到。
