49 citations · 198 across the 22 of their papers we have counts for
22 papers
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…
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…
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…
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…
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…
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…
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay
Jianbin Lin, Zhiqiang Zhang, Jun Zhou +5
Ant Credit Pay is a consumer credit service in Ant Financial Service Group. Similar to credit card, loan default is one of the major risks of this credit product. Hence, effective…
Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition
Zhigang Dai, Jinhua Fu, Qile Zhu +3
Dialogue act recognition is a fundamental task for an intelligent dialogue system. Previous work models the whole dialog to predict dialog acts, which may bring the noise from unre…
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization
Chaochao Chen, Ziqi Liu, Peilin Zhao +2
Points of interest (POI) recommendation has been drawn much attention recently due to the increasing popularity of location-based networks, e.g., Foursquare and Yelp. Among the exi…
Long Short-Term Sample Distillation
Liang Jiang, Zujie Wen, Zhongping Liang +7
In the past decade, there has been substantial progress at training increasingly deep neural networks. Recent advances within the teacher--student training paradigm have establishe…
Uncovering Insurance Fraud Conspiracy with Network Learning
Chen Liang, Ziqi Liu, Bin Liu +4
Fraudulent claim detection is one of the greatest challenges the insurance industry faces. Alibaba's return-freight insurance, providing return-shipping postage compensations over…
Heterogeneous Graph Neural Networks for Malicious Account Detection
Ziqi Liu, Chaochao Chen, Xinxing Yang +3
We present, GEM, the first heterogeneous graph neural network approach for detecting malicious accounts at Alipay, one of the world's leading mobile cashless payment platform. Our…
How Much Can A Retailer Sell? Sales Forecasting on Tmall
Chaochao Chen, Ziqi Liu, Jun Zhou +4
Time-series forecasting is an important task in both academic and industry, which can be applied to solve many real forecasting problems like stock, water-supply, and sales predict…
A Time Attention based Fraud Transaction Detection Framework
Longfei Li, Ziqi Liu, Chaochao Chen +3
With online payment platforms being ubiquitous and important, fraud transaction detection has become the key for such platforms, to ensure user account safety and platform security…
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial
Shaosheng Cao, Xinxing Yang, Cen Chen +3
With the explosive growth of e-commerce and the booming of e-payment, detecting online transaction fraud in real time has become increasingly important to Fintech business. To tack…
Review Helpfulness Prediction with Embedding-Gated CNN
Cen Chen, Minghui Qiu, Yinfei Yang +4
Product reviews, in the form of texts dominantly, significantly help consumers finalize their purchasing decisions. Thus, it is important for e-commerce companies to predict review…
Distributed Collaborative Hashing and Its Applications in Ant Financial
Chaochao Chen, Ziqi Liu, Peilin Zhao +3
Collaborative filtering, especially latent factor model, has been popularly used in personalized recommendation. Latent factor model aims to learn user and item latent factors from…
Feature Propagation on Graph: A New Perspective to Graph Representation Learning
Biao Xiang, Ziqi Liu, Jun Zhou +1
We study feature propagation on graph, an inference process involved in graph representation learning tasks. It's to spread the features over the whole graph to the -th orders,…
A Boosting Framework of Factorization Machine
Longfei Li, Peilin Zhao, Jun Zhou +1
Recently, Factorization Machines (FM) has become more and more popular for recommendation systems, due to its effectiveness in finding informative interactions between features. Us…
Time-sensitive Customer Churn Prediction based on PU Learning
Li Wang, Chaochao Chen, Jun Zhou +1
With the fast development of Internet companies throughout the world, customer churn has become a serious concern. To better help the companies retain their customers, it is import…
GeniePath: Graph Neural Networks with Adaptive Receptive Paths
Ziqi Liu, Chaochao Chen, Longfei Li +4
We present, GeniePath, a scalable approach for learning adaptive receptive fields of neural networks defined on permutation invariant graph data. In GeniePath, we propose an adapti…
Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier
Zhiming Wang, Xiaolong Li, Jun Zhou
Mainly for the sake of solving the lack of keyword-specific data, we propose one Keyword Spotting (KWS) system using Deep Neural Network (DNN) and Connectionist Temporal Classifier…