activity
20172021
most citedUncovering Insurance Fraud Conspiracy with Network Learning

49 citations · 109 across the 12 of their papers we have counts for

collaborators

22 papers

cs.AI20212 cited

R4: A Framework for Route Representation and Route Recommendation

Ran Cheng, Chao Chen, Longfei Xu +5

Route recommendation is significant in navigation service. Two major challenges for route recommendation are route representation and user representation. Different from items that…

cs.IR20214 cited

Denoising User-aware Memory Network for Recommendation

Zhi Bian, Shaojun Zhou, Hao Fu +6

For better user satisfaction and business effectiveness, more and more attention has been paid to the sequence-based recommendation system, which is used to infer the evolution of…

cs.CL2020

Interactive Question Clarification in Dialogue via Reinforcement Learning

Xiang Hu, Zujie Wen, Yafang Wang +2

Coping with ambiguous questions has been a perennial problem in real-world dialogue systems. Although clarification by asking questions is a common form of human interaction, it is…

cs.CL20205 cited

LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding

Hao Fu, Shaojun Zhou, Qihong Yang +4

The pre-training models such as BERT have achieved great results in various natural language processing problems. However, a large number of parameters need significant amounts of…

cs.IR20201 cited

RNE: A Scalable Network Embedding for Billion-scale Recommendation

Jianbin Lin, Daixin Wang, Lu Guan +5

Nowadays designing a real recommendation system has been a critical problem for both academic and industry. However, due to the huge number of users and items, the diversity and dy…

cs.LG20202 cited

Unpack Local Model Interpretation for GBDT

Wenjing Fang, Jun Zhou, Xiaolong Li +1

A gradient boosting decision tree (GBDT), which aggregates a collection of single weak learners (i.e. decision trees), is widely used for data mining tasks. Because GBDT inherits t…