24 citations · 51 across the 13 of their papers we have counts for
10 papers · 1 filter
Givens Coordinate Descent Methods for Rotation Matrix Learning in Trainable Embedding Indexes
Yunjiang Jiang, Han Zhang, Yiming Qiu +3
Product quantization (PQ) coupled with a space rotation, is widely used in modern approximate nearest neighbor (ANN) search systems to significantly compress the disk storage for e…
Sequential Search with Off-Policy Reinforcement Learning
Dadong Miao, Yanan Wang, Guoyu Tang +6
Recent years have seen a significant amount of interests in Sequential Recommendation (SR), which aims to understand and model the sequential user behaviors and the interactions be…
Multi-behavior Graph Contextual Aware Network for Session-based Recommendation
Qi Shen, Lingfei Wu, Yitong Pang +4
Predicting the next interaction of a short-term sequence is a challenging task in session-based recommendation (SBR).Multi-behavior session recommendation considers session sequenc…
Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation
Yiming Zhang, Lingfei Wu, Qi Shen +5
Social recommendation based on social network has achieved great success in improving the performance of recommendation system. Since social network (user-user relations) and user-…
Deep Natural Language Processing for LinkedIn Search
Weiwei Guo, Xiaowei Liu, Sida Wang +7
Many search systems work with large amounts of natural language data, e.g., search queries, user profiles, and documents. Building a successful search system requires a thorough un…
SearchGCN: Powering Embedding Retrieval by Graph Convolution Networks for E-Commerce Search
Xinlin Xia, Shang Wang, Han Zhang +5
Graph convolution networks (GCN), which recently becomes new state-of-the-art method for graph node classification, recommendation and other applications, has not been successfully…