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Click-Through Rate Prediction

25 papers with code · Miscellaneous

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

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Greatest papers with code

FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction

23 May 2019shenweichen/DeepCTR

In this paper, a new model named FiBiNET as an abbreviation for Feature Importance and Bilinear feature Interaction NETwork is proposed to dynamically learn the feature importance and fine-grained feature interactions.

CLICK-THROUGH RATE PREDICTION FEATURE IMPORTANCE

Deep Session Interest Network for Click-Through Rate Prediction

16 May 2019shenweichen/DeepCTR

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt, Deep Session Interest Network(DSIN)

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

9 Apr 2019shenweichen/DeepCTR

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt, Deep Session Interest Network(DSIN)

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

29 Oct 2018shenweichen/DeepCTR

Afterwards, a multi-head self-attentive neural network with residual connections is proposed to explicitly model the feature interactions in the low-dimensional space.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

Deep Interest Evolution Network for Click-Through Rate Prediction

11 Sep 2018shenweichen/DeepCTR

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt

CLICK-THROUGH RATE PREDICTION

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

1 Jul 2018shenweichen/DeepCTR

User response prediction is a crucial component for personalized information retrieval and filtering scenarios, such as recommender system and web search.

CLICK-THROUGH RATE PREDICTION FEATURE ENGINEERING INFORMATION RETRIEVAL RECOMMENDATION SYSTEMS

DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction

12 Apr 2018shenweichen/DeepCTR

In this paper, we study two instances of DeepFM where its "deep" component is DNN and PNN respectively, for which we denote as DeepFM-D and DeepFM-P. Comprehensive experiments are conducted to demonstrate the effectiveness of DeepFM-D and DeepFM-P over the existing models for CTR prediction, on both benchmark data and commercial data.

CLICK-THROUGH RATE PREDICTION FEATURE ENGINEERING RECOMMENDATION SYSTEMS

xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems

14 Mar 2018shenweichen/DeepCTR

On one hand, the xDeepFM is able to learn certain bounded-degree feature interactions explicitly; on the other hand, it can learn arbitrary low- and high-order feature interactions implicitly.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

Deep & Cross Network for Ad Click Predictions

17 Aug 2017shenweichen/DeepCTR

Feature engineering has been the key to the success of many prediction models.

CLICK-THROUGH RATE PREDICTION FEATURE ENGINEERING

Deep Interest Network for Click-Through Rate Prediction

21 Jun 2017shenweichen/DeepCTR

In this way, user features are compressed into a fixed-length representation vector, in regardless of what candidate ads are.

CLICK-THROUGH RATE PREDICTION