xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems

Combinatorial features are essential for the success of many commercial models. Manually crafting these features usually comes with high cost due to the variety, volume and velocity of raw data in web-scale systems... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Click-Through Rate Prediction Bing News xDeepFM AUC 0.84 # 1
Log Loss 0.2649 # 1
Click-Through Rate Prediction Criteo xDeepFM AUC 0.8052 # 7
Log Loss 0.4418 # 4
Click-Through Rate Prediction Dianping xDeepFM AUC 0.8639 # 1
Log Loss 0.3156 # 1

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet