About

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 )

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Datasets

Latest papers with code

XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction

22 Apr 2021bigdata-ustc/XCrossNet

Motivated by this, we propose a novel Extreme Cross Network, abbreviated XCrossNet, which aims at learning dense and sparse feature interactions in an explicit manner.

CLICK-THROUGH RATE PREDICTION FEATURE ENGINEERING RECOMMENDATION SYSTEMS

0
22 Apr 2021

Automated Creative Optimization for E-Commerce Advertising

28 Feb 2021alimama-creative/AutoCO

However, interactions between creative elements may be more complex than the inner product, and the FM-estimated CTR may be of high variance due to limited feedback.

AUTOML CLICK-THROUGH RATE PREDICTION VARIATIONAL INFERENCE

0
28 Feb 2021

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning

25 Nov 2020duchao0726/DUAL

Modern online advertising systems inevitably rely on personalization methods, such as click-through rate (CTR) prediction.

CLICK-THROUGH RATE PREDICTION GAUSSIAN PROCESSES

13
25 Nov 2020

MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction

7 Aug 2020oywtece/minet

Our study is based on UC Toutiao (a news feed service integrated with the UC Browser App, serving hundreds of millions of users daily), where the source domain is the news and the target domain is the ad.

CLICK-THROUGH RATE PREDICTION

35
07 Aug 2020

User Behavior Retrieval for Click-Through Rate Prediction

28 May 2020qinjr/UBR4CTR

These retrieved behaviors are then fed into a deep model to make the final prediction instead of simply using the most recent ones.

CLICK-THROUGH RATE PREDICTION

24
28 May 2020

Deep Interest with Hierarchical Attention Network for Click-Through Rate Prediction

22 May 2020stellaxu/DHAN

Deep Interest Network (DIN) is a state-of-the-art model which uses attention mechanism to capture user interests from historical behaviors.

CLICK-THROUGH RATE PREDICTION HIERARCHICAL STRUCTURE

43
22 May 2020

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

25 Mar 2020zhuchenxv/AutoFIS

By implementing a regularized optimizer over the architecture parameters, the model can automatically identify and remove the redundant feature interactions during the training process of the model.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

113
25 Mar 2020

DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving

17 Feb 2020WayneDW/DeepLight_Deep-Lightweight-Feature-Interactions

To address the issue of significantly increased serving delay and high memory usage for ad serving in production, this paper presents \emph{DeepLight}: a framework to accelerate the CTR predictions in three aspects: 1) accelerate the model inference via explicitly searching informative feature interactions in the shallow component; 2) prune redundant layers and parameters at intra-layer and inter-layer level in the DNN component; 3) promote the sparsity of the embedding layer to preserve the most discriminant signals.

CLICK-THROUGH RATE PREDICTION

62
17 Feb 2020

FLEN: Leveraging Field for Scalable CTR Prediction

12 Nov 2019shenweichen/DeepCTR

By suitably exploiting field information, the field-wise bi-interaction pooling captures both inter-field and intra-field feature conjunctions with a small number of model parameters and an acceptable time complexity for industrial applications.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

4,840
12 Nov 2019