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Zhiyong Feng - IEEE Xplore Author Profile
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Zhiyong Feng

Also published under: ZhiYong Feng, Zhi-Yong Feng, Zhi-yong Feng

Publications
163
Citations
1,434
Publications by Year
20062025
Co-Authors:
Show All Co-Authors (393)
Image of author Zhiyong Feng

Zhiyong Feng

Also published under: ZhiYong Feng, Zhi-Yong Feng, Zhi-yong Feng

Affiliation

College of Intelligence and Computing
Tianjin University
Tianjin, China

Publication Topics

Biography

Zhiyong Feng (Member, IEEE) received the PhD degree from Tianjin University, Tianjin, China, in 1996. He is currently a professor with the College of Intelligence and Computing, Tianjin University, Tianjin, China. He has authored more than 200 articles, one book and 40 patents. His research interests include service computing, knowledge engineering, and software engineering. He is a distinguished member of China Computer Federation (CCF), a member of the Association for Computing Machinery (ACM), and the Chairman of ACM China Tianjin Branch. He has served as general chair and Program Committee chair of numerous international conferences, such as ICWS, ICSS, APWeb-WAIM, etc.(Based on document published on 2 December 2024).
Publications
163
Citations
1,434
Publications by Year
20062025
Co-Authors:
Show All Co-Authors (393)
Author's Published Works

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Improving Adversarial Transferability through Channel-wise Scaling and Frequency-random Dropping

Pei Chen;Zhiyong Feng;Meng Xing;Yiming Zhang;Jinqing Zheng

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2025 | Conference Paper |
For black-box attacks, most existing attack methods exhibit weak transferability due to the significant discrepancy between substitute model and victim model. We argue that the model-specific discriminative regions are a key factor causing overfitting to the source model. However, existing model augmentation methods focus on augmentations within a single domain, thereby restricting the diversity o...Show More

Improving Adversarial Transferability through Channel-wise Scaling and Frequency-random Dropping

Pei Chen;Zhiyong Feng;Meng Xing;Yiming Zhang;Jinqing Zheng

Year: 2025 | Conference Paper |

Self-Organization Scheduling of Dynamic UAV-MD Networks via Three-Layer Hierarchical Reinforcement Learning

Qiao Liao;Zhiyong Feng;Hongyue Wu;Shizhan Chen;Xiao Xue

IEEE Transactions on Consumer Electronics
Year: 2025 | Early Access Article |
Self-organization scheduling is a critic must to support the wide use of UAVs (Unmanned Aerial-Vehicles) in many scenarios, where frequent changes of network topology caused by high mobility of both UAVs and mobile devices (MDs) lead to great challenges. We propose a self-organization scheduling architecture of dynamic UAV-MD networks containing three sub-problems, respectively for UAVs’ flight ro...Show More

Self-Organization Scheduling of Dynamic UAV-MD Networks via Three-Layer Hierarchical Reinforcement Learning

Qiao Liao;Zhiyong Feng;Hongyue Wu;Shizhan Chen;Xiao Xue

Year: 2025 | Early Access Article |

Do Chase Your Tail! Missing Key Aspects Augmentation in Textual Vulnerability Descriptions of Long-Tail Software Through Feature Inference

Linyi Han;Shidong Pan;Zhenchang Xing;Jiamou Sun;Sofonias Yitagesu;Xiaowang Zhang;Zhiyong Feng

IEEE Transactions on Software Engineering
Year: 2025 | Volume: 51, Issue: 2 | Journal Article |
Augmenting missing key aspects in Textual Vulnerability Descriptions (TVDs) is crucial for effective vulnerability analysis. For instance, in TVDs, key aspects include Attack Vector, Vulnerability Type, among others. These key aspects help security engineers understand and address the vulnerability in a timely manner. For software with a large user base (non-long-tail software), augmenting these m...Show More

Do Chase Your Tail! Missing Key Aspects Augmentation in Textual Vulnerability Descriptions of Long-Tail Software Through Feature Inference

Linyi Han;Shidong Pan;Zhenchang Xing;Jiamou Sun;Sofonias Yitagesu;Xiaowang Zhang;Zhiyong Feng

Year: 2025 | Volume: 51, Issue: 2 | Journal Article |

Optimization of Models and Strategies for Computation Offloading in the Internet of Vehicles: Efficiency and Trust

Qinghang Gao;Jianmao Xiao;Zhiyong Feng;Jingyu Li;Yang Yu;Hongqi Chen;Qiaoyun Yin

IEEE Transactions on Mobile Computing
Year: 2025 | Volume: 24, Issue: 4 | Journal Article |
With the rapid development of the Internet of Vehicles (IoV), vehicles will generate massive data and computation demands, necessitating computation offloading at the edge. However, existing research faces challenges in efficiency and trust. In this paper, we explore the IoV computation offloading from both user and edge facility provider perspectives, working to optimize the quality of experience...Show More

Optimization of Models and Strategies for Computation Offloading in the Internet of Vehicles: Efficiency and Trust

Qinghang Gao;Jianmao Xiao;Zhiyong Feng;Jingyu Li;Yang Yu;Hongqi Chen;Qiaoyun Yin

Year: 2025 | Volume: 24, Issue: 4 | Journal Article |

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms

Guoli Wu;Zhiyong Feng;Shizhan Chen;Hongyue Wu;Xiao Xue;Jianmao Xiao;Guodong Fan;Hongqi Chen;Jingyu Li

IEEE Transactions on Knowledge and Data Engineering
Year: 2025 | Volume: 37, Issue: 2 | Journal Article |
Traditional recommendation systems focus on maximizing user satisfaction by suggesting their favorite items. This user-centric approach may lead to unfair exposure distribution among the providers. On the contrary, a provider-centric design might become unfair to the users. Therefore, this paper proposes a re-ranking model FairSort1 to find a trade-off solution among user-side fairness, provider-s...Show More

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms

Guoli Wu;Zhiyong Feng;Shizhan Chen;Hongyue Wu;Xiao Xue;Jianmao Xiao;Guodong Fan;Hongqi Chen;Jingyu Li

Year: 2025 | Volume: 37, Issue: 2 | Journal Article |

A novel backdoor scenario target the vulnerability of Prompt-as-a-Service for code intelligence models

Yujie Fang;Zhiyong Feng;Guodong Fan;Shizhan Chen

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
With the rapid development of prompt tuning technologies and the emergence of prompt-as-a-service platforms, the security of prompt service has attracted the attention of researchers. Deep neural networks face susceptibility to various adversaries. A particularly malicious altering model behavior is backdoor attack, where model predictions exhibit divergence in the presence of specific triggers in...Show More

A novel backdoor scenario target the vulnerability of Prompt-as-a-Service for code intelligence models

Yujie Fang;Zhiyong Feng;Guodong Fan;Shizhan Chen

Year: 2024 | Conference Paper |

User Privacy-aware Computation Offloading in Mobile Edge Computing Systems

Hongyue Wu;Zhiwei Chen;Shizhan Chen;Zhiyong Feng

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
With the rapid development of mobile communication and Internet of Things (IoT) technologies, smart mobile devices such as portable and sensor devices have been widely used in our daily lives. However, their compact size and limited energy capacity inherently hinder their ability to efficiently handle computation-intensive tasks within acceptable timeframes. To tackle this challenge, computation o...Show More

User Privacy-aware Computation Offloading in Mobile Edge Computing Systems

Hongyue Wu;Zhiwei Chen;Shizhan Chen;Zhiyong Feng

Year: 2024 | Conference Paper |

D2D Service Provisioning Mechanism for Content Sharing

Yunfei Luo;Hongyue Wu;Dandan Li;Shizhan Chen;Zhiyong Feng

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
With the rapid development of mobile internet, mobile data traffic has increased substantially, and multimedia services have gradually occupied a large proportion of mobile network traffic. Using the Device-to-Device (D2D) technique for multimedia content sharing is considered as an effective solution to address large-scale user requests. D2D communication technology refers to direct data transmis...Show More

D2D Service Provisioning Mechanism for Content Sharing

Yunfei Luo;Hongyue Wu;Dandan Li;Shizhan Chen;Zhiyong Feng

Year: 2024 | Conference Paper |

Beyond Traditional Metrics: The Power of Value Entropy in Multidimensional Evaluation of the Service Ecosystem

Xiangning Yu;Xiao Xue;Deyu Zhou;Li Fang;Zhiyong Feng

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
With the increasing prevalence of smart services in our daily lives, service ecosystems are rapidly emerging across various domains, including E-commerce, cloud manufacturing, and crowdsourcing, among others. However, evaluating the utility of service ecosystems presents several challenges due to their complex characteristics, including the diversity in crowd intelligence, the cascading effects of...Show More

Beyond Traditional Metrics: The Power of Value Entropy in Multidimensional Evaluation of the Service Ecosystem

Xiangning Yu;Xiao Xue;Deyu Zhou;Li Fang;Zhiyong Feng

Year: 2024 | Conference Paper |

A Two-level Learning Approach for Achieving the Sustainable Development of Service Ecosystem

Chao Peng;Xiao Xue;Xuwen Zhang;Peilin Ji;Yifan Shen;Li Fang;Zhiyong Feng

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
The governance of service ecosystem needs to balance efficiency and fairness to promote the sustainable development of the system, making it an important topic. However, service entities in the service ecosystem have autonomy and engage in dynamic game with governance strategies, leading to governance challenges. To address this issue, we model the governance process as a repeated sequential game ...Show More

A Two-level Learning Approach for Achieving the Sustainable Development of Service Ecosystem

Chao Peng;Xiao Xue;Xuwen Zhang;Peilin Ji;Yifan Shen;Li Fang;Zhiyong Feng

Year: 2024 | Conference Paper |

Governance of Data Service Marketplace Under Service Ecosystem

Xinyue Zhou;Zhiyong Feng;Shizhan Chen;Xiao Xue;Hongyue Wu

2024 IEEE International Conference on Web Services (ICWS)
Year: 2024 | Conference Paper |
Data service marketplaces are pivotal elements of an intelligent society as they bridge user requirements and the realization of value from data services. Ensuring the efficient circulation of data services and driving industrial chains to create value within data service marketplaces has become a core issue in developing intelligent societies, posing an urgent concern for researchers and governme...Show More

Governance of Data Service Marketplace Under Service Ecosystem

Xinyue Zhou;Zhiyong Feng;Shizhan Chen;Xiao Xue;Hongyue Wu

Year: 2024 | Conference Paper |

Security-Oriented Architecture for Blockchain-Based Federated Learning in the Financial Industry

Zhengxin Guo;Shizhan Chen;Chao Wang;Hongyue Wu;Kai Ma;Zhiyong Feng

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
Year: 2024 | Conference Paper |
Financial institutions may be subject to financial fraud by malicious users because of the large amount of transaction data and sensitive user information involved. Therefore, it is crucial to design a machine learning model that can detect abnormal data in financial institutions. However, with the development of the economy and technology, the massive amount of user-generated data is distributed ...Show More

Security-Oriented Architecture for Blockchain-Based Federated Learning in the Financial Industry

Zhengxin Guo;Shizhan Chen;Chao Wang;Hongyue Wu;Kai Ma;Zhiyong Feng

Year: 2024 | Conference Paper |

A Vision-language Model Based on Prompt Learner for Few-shot Medical Images Diagnosis

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
Year: 2024 | Conference Paper |
In the real world, it can be challenging to annotate a large-scale dataset for all medical images, making few-shot medical image classification an important task. The latest advancements in pre-trained vision-language models as CLIP have demonstrated excellent performance in zero-shot natural image recognition and show advantages in medical applications. However, we have found that deploying such ...Show More

A Vision-language Model Based on Prompt Learner for Few-shot Medical Images Diagnosis

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

Year: 2024 | Conference Paper |

Relation-Aware Heterogeneous Graph Network for Learning Intermodal Semantics in Textbook Question Answering

Sai Zhang;Yunjie Wu;Xiaowang Zhang;Zhiyong Feng;Liang Wan;Zhiqiang Zhuang

IEEE Transactions on Neural Networks and Learning Systems
Year: 2024 | Volume: 35, Issue: 9 | Journal Article |
Textbook question answering (TQA) task aims to infer answers for given questions from a multimodal context, including text and diagrams. The existing studies have aggregated intramodal semantics extracted from a single modality but have yet to capture the intermodal semantics between different modalities. A major challenge in learning intermodal semantics is maintaining lossless intramodal semanti...Show More

Relation-Aware Heterogeneous Graph Network for Learning Intermodal Semantics in Textbook Question Answering

Sai Zhang;Yunjie Wu;Xiaowang Zhang;Zhiyong Feng;Liang Wan;Zhiqiang Zhuang

Year: 2024 | Volume: 35, Issue: 9 | Journal Article |

YOLOH: You Only Look One Hourglass for Real-Time Object Detection

Shaobo Wang;Renhai Chen;Hongyue Wu;Xiaozhe Li;Zhiyong Feng

IEEE Transactions on Image Processing
Year: 2024 | Volume: 33 | Journal Article |
Cited by: Papers (1)
Multi-scale detection based on Feature Pyramid Networks (FPN) has been a popular approach in object detection to improve accuracy. However, using multi-layer features in the decoder of FPN methods entails performing many convolution operations on high-resolution feature maps, which consumes significant computational resources. In this paper, we propose a novel perspective for FPN in which we direc...Show More

YOLOH: You Only Look One Hourglass for Real-Time Object Detection

Shaobo Wang;Renhai Chen;Hongyue Wu;Xiaozhe Li;Zhiyong Feng

Year: 2024 | Volume: 33 | Journal Article |

A Platform Ecosystem Evolution Model With Service Dynamic Supply and Matching

Xinyue Zhou;Jianmao Xiao;Xiao Xue;Shizhan Chen;Zhiyong Feng

IEEE Transactions on Computational Social Systems
Year: 2024 | Volume: 11, Issue: 3 | Journal Article |
Governance strategies related to platform ecosystems have become a vital issue for developing a smart society, attracting governments’ and practitioners’ attention. Under the consensus of “service as a commodity” and “platform as market,” service providers, platforms, services, and various supply demand matching methods form new supply processes. These elements are continuously and uncertainly cha...Show More

A Platform Ecosystem Evolution Model With Service Dynamic Supply and Matching

Xinyue Zhou;Jianmao Xiao;Xiao Xue;Shizhan Chen;Zhiyong Feng

Year: 2024 | Volume: 11, Issue: 3 | Journal Article |

5G Ultradense Cellular-Network-Based Edge Demand Response: Energy Consumption Reduction

Qinghang Gao;Jianmao Xiao;Hao Wang;Yuanlong Cao;Shuiguang Deng;Zhiyong Feng

IEEE Internet of Things Journal
Year: 2024 | Volume: 11, Issue: 7 | Journal Article |
Cited by: Papers (3)
With the development of 5G technology, ultradense cellular networks are becoming a trend, while the deployment of large-area and high-density base stations (BSs) will bring new energy consumption problems. In this article, we explore the energy consumption of the edge demand response (EDR) from the two perspectives of edge users and edge facility providers. While guaranteeing the essential Quality...Show More

5G Ultradense Cellular-Network-Based Edge Demand Response: Energy Consumption Reduction

Qinghang Gao;Jianmao Xiao;Hao Wang;Yuanlong Cao;Shuiguang Deng;Zhiyong Feng

Year: 2024 | Volume: 11, Issue: 7 | Journal Article |

Service Recommendations for Mashup Based on Generation Model

Guodong Fan;Shizhan Chen;Qiang He;Hongyue Wu;Jing Li;Xiao Xue;Zhiyong Feng

IEEE Transactions on Services Computing
Year: 2024 | Volume: 17, Issue: 4 | Journal Article |
Service recommendations are crucial for developers to create mashups such as mobile applications, workflows, e-business solutions, etc. Existing methods based on collaborative filtering or content analysis are manual and cannot automatically acquire services that align with the requirements of mashup creation. A possible solution to automatically acquiring necessary services for mashups is the seq...Show More

Service Recommendations for Mashup Based on Generation Model

Guodong Fan;Shizhan Chen;Qiang He;Hongyue Wu;Jing Li;Xiao Xue;Zhiyong Feng

Year: 2024 | Volume: 17, Issue: 4 | Journal Article |

Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning

Dongxiao He;Chundong Liang;Cuiying Huo;Zhiyong Feng;Di Jin;Liang Yang;Weixiong Zhang

IEEE Transactions on Neural Networks and Learning Systems
Year: 2024 | Volume: 35, Issue: 4 | Journal Article |
Cited by: Papers (18)
Heterogeneous information networks (HINs) are potent models of complex systems. In practice, many nodes in an HIN have their attributes unspecified, resulting in significant performance degradation for supervised and unsupervised representation learning. We developed an unsupervised heterogeneous graph contrastive learning approach for analyzing HINs with missing attributes (HGCA). HGCA adopts a c...Show More

Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning

Dongxiao He;Chundong Liang;Cuiying Huo;Zhiyong Feng;Di Jin;Liang Yang;Weixiong Zhang

Year: 2024 | Volume: 35, Issue: 4 | Journal Article |

A Self-Iteration Code Generation Method Based on Large Language Models

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)
Year: 2023 | Conference Paper |
Although large language models (LLMs) have demonstrated impressive performance in code generation, they still face challenges when dealing with complex code generation tasks. In the software development process, humans often refine complex tasks iteratively and continuously modify and improve them. Inspired by this, we propose a self-iteration code generation framework based on large language mode...Show More

A Self-Iteration Code Generation Method Based on Large Language Models

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

Year: 2023 | Conference Paper |

RTCoder: An Approach based on Retrieve-template for Automatic Code Generation

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)
Year: 2023 | Conference Paper |
Regarding code generation, researchers have recently proposed a retrieve-template-generation approach. This method involves retrieving similar code snippets through a retriever and providing them to a generator along with input descriptions. However, since the retrieved similar code can be influenced by various data types, it may lead the model to reference unrelated content, resulting in some dis...Show More

RTCoder: An Approach based on Retrieve-template for Automatic Code Generation

Tianyou Chang;Shizhan Chen;Guodong Fan;Zhiyong Feng

Year: 2023 | Conference Paper |

Building a Decentralized Crowdsourcing System with Blockchain as a Service

Gaoyong Han;Zhiyong Feng;Yanwei Xu;Xiao Xue;Shizhan Chen

2023 IEEE International Conference on Web Services (ICWS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The conventional crowdsourcing system is dependent on a centralized platform, which grants the platform owner undue authority to manipulate the operation of the system for unethical profits. In this paper, the crowdsourcing system is revolutionized in a decentralized manner with Blockchain as a Service (BaaS). All crowdsourcing operations are implemented with smart contracts deployed on blockchain...Show More

Building a Decentralized Crowdsourcing System with Blockchain as a Service

Gaoyong Han;Zhiyong Feng;Yanwei Xu;Xiao Xue;Shizhan Chen

Year: 2023 | Conference Paper |

Evolving Graph Contrastive Learning for Socially-aware Recommendation

Hongqi Chen;Zhiyong Feng;Shizhan Chen;Xiao Xue;Hongyue Wu;Yingchao Sun;Gaoyong Han;Yanwei Xu

2023 IEEE International Conference on Web Services (ICWS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Social recommendations play a crucial role in providing personalized services to users by leveraging social relationships and user sessions. Despite recent advancements, it still faces challenges in dealing with social inconsistency and the loss of critical semantic information in user-service interactions. To overcome these problems, an Evolving Graph Contrastive Learning for Socially-aware Recom...Show More

Evolving Graph Contrastive Learning for Socially-aware Recommendation

Hongqi Chen;Zhiyong Feng;Shizhan Chen;Xiao Xue;Hongyue Wu;Yingchao Sun;Gaoyong Han;Yanwei Xu

Year: 2023 | Conference Paper |

ITS: Improved Tabu Search Algorithm for Path Planning in UAV-Assisted Edge Computing Systems

Hongyue Wu;Mengchen Wu;Wen Peng;Shizhan Chen;Zhiyong Feng

2023 IEEE International Conference on Web Services (ICWS)
Year: 2023 | Conference Paper |
Cited by: Papers (7)
Mobile Edge Computing (MEC) plays a crucial role in providing diverse computation and storage services to intelligent equipment. In recent years, the utilization of Unmanned Aerial Vehicles (UAVs) equipped with edge servers has emerged as a promising approach to enable ubiquitous edge computing services. This paradigm offers various benefits, such as reduced latency and flexible service provisioni...Show More

ITS: Improved Tabu Search Algorithm for Path Planning in UAV-Assisted Edge Computing Systems

Hongyue Wu;Mengchen Wu;Wen Peng;Shizhan Chen;Zhiyong Feng

Year: 2023 | Conference Paper |

Cost-Efficient Request Bundling for O2O Home Services

Ruoshan Zang;Zhiyong Feng;Xinyue Zhou;Shizhan Chen;Xiao Xue;Hongyue Wu;Hongqi Chen

2023 IEEE International Conference on Web Services (ICWS)
Year: 2023 | Conference Paper |
With the advent of mobile internet, Online-to-Offline (O2O) home services have emerged, such as home healthcare and repair services, greatly facilitating our lives. Customers book services through online platforms, and workers provide the requested services at the customers’ homes offline. However, each time workers travel to customers’ homes, they incur opportunity cost, leading to increased cost...Show More

Cost-Efficient Request Bundling for O2O Home Services

Ruoshan Zang;Zhiyong Feng;Xinyue Zhou;Shizhan Chen;Xiao Xue;Hongyue Wu;Hongqi Chen

Year: 2023 | Conference Paper |

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