120 citations · 241 across the 18 of their papers we have counts for
19 papers
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
Sheng Xiang, Mingzhi Zhu, Dawei Cheng +5
Credit card fraud incurs a considerable cost for both cardholders and issuing banks. Contemporary methods apply machine learning-based classifiers to detect fraudulent behavior fro…
MCSCSet: A Specialist-annotated Dataset for Medical-domain Chinese Spelling Correction
Wangjie Jiang, Zhihao Ye, Zijing Ou +7
Chinese Spelling Correction (CSC) is gaining increasing attention due to its promise of automatically detecting and correcting spelling errors in Chinese texts. Despite its extensi…
Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning
Yi Cheng, Wenge Liu, Wenjie Li +5
Providing Emotional Support (ES) to soothe people in emotional distress is an essential capability in social interactions. Most existing researches on building ES conversation syst…
"My nose is running.""Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics
Wenge Liu, Yi Cheng, Hao Wang +6
With the rise of telemedicine, the task of developing Dialogue Systems for Medical Diagnosis (DSMD) has received much attention in recent years. Different from early researches tha…
Privacy-preserving Anomaly Detection in Cloud Manufacturing via Federated Transformer
Shiyao Ma, Jiangtian Nie, Jiawen Kang +5
With the rapid development of cloud manufacturing, industrial production with edge computing as the core architecture has been greatly developed. However, edge devices often suffer…
Tell Me How to Survey: Literature Review Made Simple with Automatic Reading Path Generation
Jiayuan Ding, Tong Xiang, Zijing Ou +5
Recent years have witnessed the dramatic growth of paper volumes with plenty of new research papers published every day, especially in the area of computer science. How to glean pa…
Refining BERT Embeddings for Document Hashing via Mutual Information Maximization
Zijing Ou, Qinliang Su, Jianxing Yu +3
Existing unsupervised document hashing methods are mostly established on generative models. Due to the difficulties of capturing long dependency structures, these methods rarely mo…
Prototypical Graph Contrastive Learning
Shuai Lin, Pan Zhou, Zi-Yuan Hu +6
Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. But in practice, precise graph annotations are generall…
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval
Zijing Ou, Qinliang Su, Jianxing Yu +5
With the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval. To generate high-quality ha…
Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting
Yi Cheng, Siyao Li, Bang Liu +4
This paper explores the task of Difficulty-Controllable Question Generation (DCQG), which aims at generating questions with required difficulty levels. Previous research on this ta…
Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management
Zhengxu Hou, Bang Liu, Ruihui Zhao +4
For task-oriented dialog systems, training a Reinforcement Learning (RL) based Dialog Management module suffers from low sample efficiency and slow convergence speed due to the spa…
Enquire One's Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion
Suyuchen Wang, Ruihui Zhao, Xi Chen +2
Taxonomy is a hierarchically structured knowledge graph that plays a crucial role in machine intelligence. The taxonomy expansion task aims to find a position for a new term in an…
Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation
Shuai Lin, Pan Zhou, Xiaodan Liang +4
Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledge-grounded di…
Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Yi Liu, Ruihui Zhao, Jiawen Kang +3
Federated Edge Learning (FEL) allows edge nodes to train a global deep learning model collaboratively for edge computing in the Industrial Internet of Things (IIoT), which signific…
Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses
Yi Liu, Xingliang Yuan, Ruihui Zhao +3
Semi-supervised Federated Learning (SSFL) has recently drawn much attention due to its practical consideration, i.e., the clients may only have unlabeled data. In practice, these S…
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
Ce Ju, Ruihui Zhao, Jichao Sun +11
Prevention of stroke with its associated risk factors has been one of the public health priorities worldwide. Emerging artificial intelligence technology is being increasingly adop…
Lightweight Efficient Multi-keyword Ranked Search over Encrypted Cloud Data using Dual Word Embeddings
Ruihui Zhao, Mizuho Iwaihara
Cloud computing is emerging as a revolutionary computing paradigm which pro-vides a flexible and economic strategy for data management and resource sharing. Security and privacy be…
A Privacy-preserving Community-based P2P OSNs Using Broadcast Encryption Supporting Recommendation Mechanism
Ruihui Zhao, Mingjie Ding, Keiichi Koyanagi +2
Online Social Networks (OSNs) have become one of the most important activities on the Internet, such as Facebook and Google+. However, security and privacy have become major concer…
LRSE: A Lightweight Efficient Searchable Encryption Scheme using Local and Global Representations
Ruihui Zhao, Yuanliang Sun, Mizuho Iwaihara
Cloud computing is emerging as a revolutionary computing paradigm, while security and privacy become major concerns in the cloud scenario. For which Searchable Encryption (SE) tech…