-
SearchGCN: Powering Embedding Retrieval by Graph Convolution Networks for E-Commerce Search
Graph convolution networks (GCN), which recently becomes new state-of-th...
07/01/2021 ∙ by Xinlin Xia, et al. ∙
0
∙
share
read it
-
Joint Learning of Deep Retrieval Model and Product Quantization based Embedding Index
Embedding index that enables fast approximate nearest neighbor(ANN) sear...
05/09/2021 ∙ by Han Zhang, et al. ∙
0
∙
share
read it
-
Query Rewriting via Cycle-Consistent Translation for E-Commerce Search
Nowadays e-commerce search has become an integral part of many people's ...
03/01/2021 ∙ by Yiming Qiu, et al. ∙
0
∙
share
read it
-
Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search
Result relevance prediction is an essential task of e-commerce search en...
01/13/2021 ∙ by Ziyang Liu, et al. ∙
0
∙
share
read it
-
BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search
Relevance has significant impact on user experience and business profit ...
10/20/2020 ∙ by Yunjiang Jiang, et al. ∙
0
∙
share
read it
-
Kalman Filtering Attention for User Behavior Modeling in CTR Prediction
Click-through rate (CTR) prediction is one of the fundamental tasks for ...
10/02/2020 ∙ by Hu Liu, et al. ∙
0
∙
share
read it
-
Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint
Product search is the most common way for people to satisfy their shoppi...
07/24/2020 ∙ by Zhuojian Xiao, et al. ∙
6
∙
share
read it
-
Category-Specific CNN for Visual-aware CTR Prediction at JD.com
As one of the largest B2C e-commerce platforms in China, JD.com also pow...
06/18/2020 ∙ by Hu Liu, et al. ∙
0
∙
share
read it
