Modularizing Deep Neural Network-Inspired Recommendation Algorithms

被引:0
作者
Yang, Longqi [1 ]
Bagdasaryan, Eugene [1 ]
Wen, Hongyi [1 ]
机构
[1] Cornell Univ, Cornell Tech, New York, NY 10044 USA
来源
12TH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS) | 2018年
基金
美国国家科学基金会;
关键词
Recommendation; Modularization; Deep Learning; OpenRec;
D O I
10.1145/3240323.3241618
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This tutorial reviews recent developments of deep neural network-based recommendation algorithms and demonstrates how to extend and adapt such algorithms for diverse application scenarios. The customization is supported by OpenRec framework that modularizes neural recommenders. The tutorial consists of a lecture and two hands-on sessions. It targets intermediate and advanced audiences who already possess knowledge of deep neural networks and are interested in applying those knowledge to the domain of recommendation. Materials are available at: http://openrec.ai/
引用
收藏
页码:533 / 534
页数:2
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