Click-Through Rate Prediction

Click-through rate prediction is the task of predicting the likelihood that something on a website (such as an advertisement) will be clicked.

( Image credit: Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 326–350 of 391 papers

Title	Date	Tasks	Status	Hype
Deep Interaction Machine: A Simple but Effective Model for High-order Feature Interactions	Jan 1, 2020	Click-Through Rate PredictionFeature Engineering	—Unverified	0
Learning Feature Interactions with Lorentzian Factorization Machine	Nov 22, 2019	Click-Through Rate PredictionDeep Learning	—Unverified	0
FLEN: Leveraging Field for Scalable CTR Prediction	Nov 12, 2019	Click-Through Rate PredictionPrediction	CodeCode Available	2
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction	Nov 3, 2019	Click-Through Rate PredictionPrediction	—Unverified	0
Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction	Oct 15, 2019	Click-Through Rate PredictionMulti-Task Learning	—Unverified	0
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction	Oct 12, 2019	Click-Through Rate PredictionRecommendation Systems	CodeCode Available	1
DeepEnFM: Deep neural networks with Encoder enhanced Factorization Machine	Sep 25, 2019	Click-Through Rate Prediction	—Unverified	0
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems	Sep 25, 2019	Click-Through Rate PredictionCollaborative Filtering	CodeCode Available	0
Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions	Sep 7, 2019	Click-Through Rate Prediction	CodeCode Available	0
An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation	Aug 12, 2019	Click-Through Rate PredictionKnowledge Graphs	CodeCode Available	0
Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction	Jul 15, 2019	Click-Through Rate Prediction	—Unverified	0
Click-Through Rate Prediction with the User Memory Network	Jul 9, 2019	Click-Through Rate PredictionPrediction	CodeCode Available	0
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling	Jun 25, 2019	Click-Through Rate Prediction	—Unverified	0
Representation Learning-Assisted Click-Through Rate Prediction	Jun 11, 2019	Click-Through Rate PredictionPrediction	CodeCode Available	0
Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction	Jun 10, 2019	Click-Through Rate PredictionPrediction	CodeCode Available	0
Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions	May 26, 2019	BIG-bench Machine LearningClick-Through Rate Prediction	—Unverified	0
FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction	May 23, 2019	Click-Through Rate PredictionFeature Importance	CodeCode Available	1
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction	May 22, 2019	Click-Through Rate PredictionRecommendation Systems	CodeCode Available	0
Deep Session Interest Network for Click-Through Rate Prediction	May 16, 2019	Click-Through Rate PredictionDeep Learning	CodeCode Available	0
FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine	May 15, 2019	Click-Through Rate PredictionFeature Importance	CodeCode Available	0
Behavior Sequence Transformer for E-commerce Recommendation in Alibaba	May 15, 2019	Click-Through Rate PredictionRecommendation Systems	CodeCode Available	2
Learning Representations of Categorical Feature Combinations via Self-Attention	May 1, 2019	Click-Through Rate Prediction	—Unverified	0
Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings	Apr 25, 2019	Click-Through Rate PredictionMeta-Learning	CodeCode Available	1
CPM-sensitive AUC for CTR prediction	Apr 23, 2019	Click-Through Rate PredictionPrediction	—Unverified	0
Block-distributed Gradient Boosted Trees	Apr 23, 2019	Click-Through Rate PredictionLearning-To-Rank	—Unverified	0

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All datasets Criteo Avazu Company*Bing News iPinYou KKBox MovieLens 1M MovieLens 20M Amazon Dianping Frappe KDD12

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	QNN-α	AUC	0.82	—	Unverified
2	FCN	AUC	0.82	—	Unverified
3	GDCN	AUC	0.82	—	Unverified
4	MemoNet	AUC	0.82	—	Unverified
5	TF4CTR	AUC	0.82	—	Unverified
6	FinalMLP + MMBAttn	AUC	0.81	—	Unverified
7	FinalMLP	AUC	0.81	—	Unverified
8	CETN	AUC	0.81	—	Unverified
9	DNN + MMBAttn	AUC	0.81	—	Unverified
10	STEC	AUC	0.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OptInter	AUC	0.81	—	Unverified
2	OptInter-M	AUC	0.81	—	Unverified
3	CELS	AUC	0.8	—	Unverified
4	FCN	AUC	0.8	—	Unverified
5	CETN	AUC	0.8	—	Unverified
6	OptFS	AUC	0.8	—	Unverified
7	OptEmbed	AUC	0.79	—	Unverified
8	Sparse Deep FwFM	AUC	0.79	—	Unverified
9	FGCNN+IPNN	AUC	0.79	—	Unverified
10	Fi-GNN	AUC	0.78	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepFM	AUC	0.87	—	Unverified
2	FNN	AUC	0.87	—	Unverified
3	Wide & Deep (LR & DNN)	AUC	0.87	—	Unverified
4	PNN*	AUC	0.87	—	Unverified
5	IPNN	AUC	0.87	—	Unverified
6	Wide & Deep (FM & DNN)	AUC	0.87	—	Unverified
7	OPNN	AUC	0.87	—	Unverified
8	DeepMCP	AUC	0.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	xDeepFM	AUC	0.84	—	Unverified
2	Wide & Deep	AUC	0.84	—	Unverified
3	DeepFM	AUC	0.84	—	Unverified
4	PNN	AUC	0.83	—	Unverified
5	RippleNet	AUC	0.68	—	Unverified
6	DKN	AUC	0.66	—	Unverified
7	DNN	AUC	0.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPNN	AUC	0.82	—	Unverified
2	IPNN	AUC	0.79	—	Unverified
3	FCN	AUC	0.79	—	Unverified
4	OptInter	AUC	0.78	—	Unverified
5	OptInter-M	AUC	0.78	—	Unverified
6	PNN*	AUC	0.77	—	Unverified
7	FNN	AUC	0.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FCN	AUC	0.86	—	Unverified
2	DeepIM	AUC	0.85	—	Unverified
3	xDeepFM	AUC	0.85	—	Unverified
4	AutoInt+	AUC	0.85	—	Unverified
5	DCNv2	AUC	0.85	—	Unverified
6	DeepFM	AUC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STEC	AUC	0.97	—	Unverified
2	KNI	AUC	0.94	—	Unverified
3	RippleNet	AUC	0.92	—	Unverified
4	MKR	AUC	0.92	—	Unverified
5	DCNv3	AUC	0.91	—	Unverified
6	AutoInt	AUC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	github.com/guotong1988/movielens_dataset	AUC	0.79	—	Unverified
2	DIN + Dice Activation	AUC	0.73	—	Unverified
3	DIN	AUC	0.73	—	Unverified
4	DeepFM	AUC	0.73	—	Unverified
5	PNN	AUC	0.73	—	Unverified
6	Wide & Deep	AUC	0.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DIN + Dice Activation	AUC	0.89	—	Unverified
2	DIN	AUC	0.88	—	Unverified
3	DeepFM	AUC	0.87	—	Unverified
4	PNN	AUC	0.87	—	Unverified
5	Wide & Deep	AUC	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	xDeepFM	AUC	0.86	—	Unverified
2	DeepFM	AUC	0.85	—	Unverified
3	PNN	AUC	0.84	—	Unverified
4	Wide & Deep	AUC	0.84	—	Unverified
5	DNN	AUC	0.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TF4CTR	AUC	0.99	—	Unverified
2	FinalMLP + MMBAttn	AUC	0.99	—	Unverified
3	FinalMLP	AUC	0.99	—	Unverified
4	DNN + MMBAttn	AUC	0.99	—	Unverified
5	AFN+	AUC	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FCN	AUC	0.81	—	Unverified
2	MemoNet	AUC	0.81	—	Unverified
3	OptEmbed	AUC	0.8	—	Unverified
4	OptFS	AUC	0.8	—	Unverified
5	AutoInt	AUC	0.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TF4CTR	AUC	0.97	—	Unverified
2	FinalMLP	AUC	0.97	—	Unverified
3	AFN+	AUC	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DSTN-I	AUC	0.84	—	Unverified
2	DeepMCP	AUC	0.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	KGCN-sum	AUC	0.74	—	Unverified
2	RippleNet	AUC	0.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	KGCN-concat	AUC	0.8	—	Unverified
2	MKR	AUC	0.69	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DIEN	AUC	0.78	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NormDNN	AUC	0.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MKR	AUC	0.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FGCNN+IPNN	AUC	0.94	—	Unverified