2.6　本章小结

本章对工业级推荐系统的5种范式、算法业务流程、具体召回和排序算法做了概述，希望读者知道每类推荐范式有哪些可用的算法，各个推荐范式的应用场景，以及相关算法的实现思路。在后续章节中，我们会详细讲解主流核心算法的实现细节。

参考文献

[1]Chao Li，Zhiyuan Liu，Mengmeng Wu，et al.Multi-Interest Network with Dynamic Routing for Recommendation at Tmall[C].[S.l.]:Arxiv，2019.

[2]Chao Li，Zhiyuan Liu，Mengmeng Wu，et al.Deep Session Interest Network for Click-Through Rate Prediction[C].[S.l.]:IJCAI，2019.

[3]Qiwei Chen，Huan Zhao，Wei Li，et al.Behavior Sequence Transformer for E-commerce Recommendation in Alibaba[C].[S.l.]:Arxiv，2019.

[4]Jizhe Wang，Pipei Huang，Huan Zhao，et al.Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba[C].[S.l.]:Arxiv，2018.

[5]Sai Wu，Weichao Ren，Chengchao Yu，et al.Personal Recommendation Using Deep Recurrent Neural Networks in NetEase[C].[S.l.]:IEEE，2016.

[6]Xiangyu Zhao，Liang Zhang，Long Xia，et al.Tang Deep Reinforcement Learning for List-wise Recommendations[C].[S.l.]:Arxiv，2018.

[7]Xiangyu Zhao，Liang Zhang，Zhuoye Ding，et al.Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning[C].[S.l.]:ACM SIGKDD International Conference on Knowledge Discovery & Data Mining，2018.

[8]Han Zhu，Xiang Li，Pengye Zhang，et al.Learning Tree-based Deep Model for Recommender Systems[C].[S.l.]:KDD，2018.

[9]Oren Barkan，Noam Koenigstein.Item2Vec:Neural Item Embedding for Collaborative Filtering[C].[S.l.]:Arxiv，2014.

[10]Paul Covington，Jay Adams，Emre Sargin.Deep Neural Networks for YouTube Recommendations[C].[S.l.]:ACM，2016.

[11]Shuai Zhang，Lina Yao，Aixin Sun，et al.Deep Learning based Recommender System:A Survey and New Perspectives[C].[S.l.]:ACM，2019.

[12]Heng-Tze Cheng，Levent Koc，Jeremiah Harmsen，et al.Wide & Deep Learning for Recommender Systems[C].[S.l.]:Arxiv，2016.

[13]Kun Gai，Xiaoqiang Zhu，Han Li，et al.Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction[C].[S.l.]:Arxiv，2017.

[14]H Brendan McMahan，Gary Holt，D Sculley，et al.Ad Click Prediction:a View from the Trenches[C].[S.l.]:ACM，2013.

[15]Jerome H Friedman.Greedy function approximation:a gradient boosting machine[C].[S.l.]:The Annals of Statistics，2001.

[16]Xinran He，Junfeng Pan，Ou Jin，et al.Practical Lessons from Predicting Clicks on Ads at Facebook[C].[S.l.]:ADKDD，2014.

[17]Abhinandan Das，Mayur Datar，Ashutosh Garg，et al.Google News Personalization:Scalable Online Collaborative Filtering[C].[S.l.]:WWW，2007.