DeepCTR

Add Models

year	paper	keyword	ref code
2020	Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution
2020	A Sparse Deep Factorization Machine for Efficient CTR prediction		https://github.com/WayneDW/sDeepFwFM
2020	Deep Match to Rank Model for Personalized Click-Through Rate		https://github.com/lvze92/DMR
2019	Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction		https://github.com/CRIPAC-DIG/Fi_GNNs
2019	Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction
2019	Deep Spatio-Temporal Neural Networks for Click-Through Rate		https://github.com/oywtece/dstn
2019	Click-Through Rate Prediction with the User Memory Network		https://github.com/rener1199/deep_memory

Add tensorflow estimator API

DeepMatch

Add Models

year	paper	keyword	ref code
2017	Neural attentive session-based recommendation
2018	Learning from history and present: next-item recommendation via discrimina- tively exploiting user behaviors.

GraphEmbedding

• add unsupervised loss function form for GraphSage

GNN in Rec

• build a pipline including the complete training and evaluation process of NGCF, GCMC and GraphSage on the specified data set