Browse > Miscellaneous > Click-Through Rate Prediction

Click-Through Rate Prediction

16 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.

State-of-the-art leaderboards

Greatest papers with code

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

29 Oct 2018shenweichen/DeepCTR

Our proposed algorithm is very general, which can be applied to both numerical and categorical input features.

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 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 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

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

Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction

18 Apr 2017shenweichen/DeepCTR

CTR prediction in real-world business is a difficult machine learning problem with large scale nonlinear sparse data.

CLICK-THROUGH RATE PREDICTION

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

13 Mar 2017shenweichen/DeepCTR

Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

Product-based Neural Networks for User Response Prediction

1 Nov 2016shenweichen/DeepCTR

Predicting user responses, such as clicks and conversions, is of great importance and has found its usage in many Web applications including recommender systems, web search and online advertising.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS