2024

• [TCSS] Yuchang Zhu, Jintang Li, Liang Chen*, Zibin Zheng, Mingdong Tang. “A Review-level Sentiment Information Enhanced Multi-task Learning Approach for Explainable Recommendation”, IEEE Transactions on Computational Social Systems, April 2024, accepted.
  [SCI Impact Factor=5.0]
• [TCSS] Fenfang Xie, Yuansheng Wang, Kun Xu, Liang Chen*, Zibin Zheng, Mingdong Tang. “A Review-level Sentiment Information Enhanced Multi-task Learning Approach for Explainable Recommendation”, IEEE Transactions on Computational Social Systems, March 2024, accepted.
  [SCI Impact Factor=5.0]
• [WWW] Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen*. “Fair Graph Representation Learning via Sensitive Attribute Disentanglement”, In Proceedings of International World Wide Web Conference, May 13th-17th, Singapore, accepted. [CCF-A]
• [ICLR] Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen*. “A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks”, In Proceedings of International Conference on Learning Representations, May 7th-11th, 2024, Vienna, Austria, accepted. [CCF-A]

2023

• [WSDM] Yuchang Zhu, Jintang Li, Liang Chen*, Zibin Zheng. “The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation”, the 17th ACM International Conference Web Search and Data Mining, Mar, 2024, pp. 1012-1021.
• [WSDM] Wangbin Sun, Jintang Li, Liang Chen*, Yatao Bian, Bingzhe wu, and Zibin Zheng. “Rethinking and Simplifying Bootstrapped Graph Latents”, the 17th ACM International Conference Web Search and Data Mining, Mar, 2024, pp. 665-673.
• [EMNLP] Wang HaoTian, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, and Bingzhe wu, “RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data”, the 2023 Conference on Empirical Methods in Natural Language Processing, Dec, 2023, pp. 7246-7257.
• [ICDM] Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen*, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, and Zibin Zheng, “Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding”, the 23rd IEEE International Conference on Data Mining(ICDM), Dec, 2023, pp. 190-199.
• [CollaborateCom] Ruoting Wu, Yuxin Zhang, Liang Chen*, “Improving Code Representation Learning via Multi-view Contrastive Graph Pooling for Abstract Syntax Tree”, CollaborateCom 2023: Collaborative Computing: Networking, Applications and Worksharing, pp. 392–413
• [CollaborateCom] Yuxin Zhang, Ruoting Wu, Jie Liao, Liang Chen*, “Structural Adversarial Attack for Code Representation Models”, In: Gao, H., Wang, X., Voros, N. (eds) CollaborateCom 2023: Collaborative Computing: Networking, Applications and Worksharing, pp. 242–261
• [CIKM] Jie Liao, Jintang Li, Liang Chen*, Bingzhe Wu, Yatao Bian and Zibin Zheng, “SAILOR: Structural Augmentation Based Tail Node Representation Learning”, the 32nd ACM International Conference on Information and Knowledge Management, October 2023, pp. 1389–1399.
• [CIKM] Jintang Li, Jie Liao, Ruofan Wu, Liang Chen*, Zibin Zheng, Jiawang Dan, Changhua Meng and Weiqiang Wang, “GUARD: Graph Universal Adversarial Defense”, the 32nd ACM International Conference on Information and Knowledge Management, October 2023, pp. 1198–1207.
• [KDD] Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen*, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang, “What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders”, the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 2023, pp. 1268–1279. [CCF-A]
• [ACM-TURC] Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu and Liang Chen*, “Attention Paper: How Generative AI Reshapes Digital Shadow Industry?”, In Proceedings of the ACM Turing Award Celebration Conference - China 2023 (ACM TURC ‘23). Association for Computing Machinery, New York, NY, USA, pp. 143–144.
• [IJCAI] Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen, “SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs”, The 32nd International Joint Conference on Artificial Intelligence, August 2023, pp. 2306-2314. [CCF-A]
• [SIGIR] Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen and Hongzhi Yin, “Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures”, the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 2023, pp. 1690-1699. [CCF-A]
• [TKDE] Jintang Li, Tao Xie, Liang Chen*, Fenfang Xie, Xiangnan He, Zibin Zheng, “Adversarial Attack on Large Scale Graph”, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 1, pp. 82-95, 1 Jan. 2023, doi: 10.1109/TKDE.2021.3078755. [CCF-A]
  [SCI Impact Factor=6.977]
• [ICDE] Yang Liu, Liang Chen*, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang, “Modelling High-Order Social Relations for Item Recommendation”, ICDE 2023 TKDE Poster session, Anaheim, California, USA, April 3 – 7, 2023, accepted.[CCF-A]
• [TKDE] Tingting Liang, Congying Xia, Haoran Xu, Ziqiang Zhao, Yuyu Yin, Liang Chen, and Philip S. Yu, “Modeling Reviews for Few-shot Recommendation via Enhanced Prototypical Network”, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 9, pp. 9407-9420, 1 Sept. 2023, doi: 10.1109/TKDE.2023.3239169.[CCF-A]
  [SCI Impact Factor=6.977]
• [AAAI] Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen*, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng, “Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks”, 37th AAAI Conference on Artificial Intelligence, Vol. 37, Issue 7, pp.8588-8596.[CCF-A]
• [ICDE] Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang, “Dynamic Activation of Clents and Parameters for Federated Learning over Heterogeneous Graphs”, 39th IEEE International Conference on Data Engineering, Anaheim, California, USA, April 2023, pp.1597-1610.[CCF-A]

2022

• [TKDE] Jintang Li, Jiaying Peng, Liang Chen*, Zibin Zheng, Tingting Liang, Qing Ling, “Spectral Adversarial Training for Robust Graph Neural Network”, IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2022.3222207.[CCF-A]
  [SCI Impact Factor=6.977]
• [TKDE] Yang Liu, Liang Chen*, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang, “Modelling High-Order Social Relations for Item Recommendation”, in IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 9, pp. 4385-4397, 1 Sept. 2022, doi: 10.1109/TKDE.2020.3039463.[CCF-A]
  [SCI Impact Factor=6.977]
• [FedGraph] Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang, “Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs”, The 1st International Workshop on Federated Learning with Graph Data at ACM CIKM, Atlanta, Georgia, United States, Oct 21, 2022.
• [KBS] Zhouxin Yu, Jintang Li, Liang Chen* and Zibin Zheng, “Unifying Multi-associations through Hypergraph for Bundle Recommendation”,Knowledge-based Systems, August 2022, vol 255, pp. 109755.[SCI Impact Factor=8.038][中科院一区]
• [KDD] Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang, “Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection”, Washington DC, USA, August 14-18, 2022, pp. 4838-4839. [Slide][Tutorial][CCF-A]
• [IJCAI] Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen*, Qi Yu, Siqiang Luo, “Spiking Graph Convolutional Networks”, 31th International Joint Conference on Artificial Intelligence, Main Track, Vienna, Australia, July 23-29, 2022, pp. 2434-2240. [Long Oral][CCF-A]
• [Arxiv] RuotingWu, Yuxin Zhang, QibiaoPeng, Liang Chen*, Zibin Zheng, “A Survey of Deep Learning Models for Structural Code Understanding”, arxiv, May 2022.[PDF]
• [KBS] Liang Chen, Tao Xie, Jintang Li, and Zibin Zheng, “Graph Enhanced Neural Interaction Model”, Knowledge-based Systems, March 2022, vol 246, pp. 108616.
  [SCI Impact Factor=8.038][中科院一区]

2021

• [CIKM] Kun Xu, Yuanzhen Xie, Liang Chen* and Zibin Zheng, “Expanding Relationship for Cross Domain Recommendation”, 30th ACM International Conference on Information and Knowledge Management, Research Track, Gold Coast, Australia, Nov 1 - 5, 2021, pp. 2251-2260.
• [TOIS] Minghao Zhao, Qilin Deng, Kai Wang, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui, “Bilateral Filtering Graph Convolutional Network for Social Recommendation in Power-Law Networks”, ACM Transactions on Information Systems, Vol 40, Issue 2, pp. 1-24. [CCF-A]
  [SCI Impact Factor=4.479]
• [IJCAI] Liang Chen, Jintang Li, Qibiao Peng , Yang Liu, Zibin Zheng, Carl Yang, “Understanding Structural Vulnerability in Graph Convolutional Networks”, 30th International Joint Conference on Artificial Intelligence, Main Track, Montreal-themed Virtual Reality, Canada, 2021, pp.2249-2255. [CCF-A]
• [IJCAI] Carl Yang, Haonan Wang, Ke Zhang, Liang Chen, Lichao Sun, “Secure Graph Generation with Link Privacy”, 30th International Joint Conference on Artificial Intelligence, Main Track, Montreal-themed Virtual Reality, Canada, 2021, pp. 3271-3278. [CCF-A]
• [SIGIR] Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie, “Self-supervised Graph Learning for Recommendation”, 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Research Paper, July 2021, pp. 726–735. [CCF-A]
• [SIGIR] Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang, “AutoDebias: Learning to Debias for Recommendation”, 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Research Paper, July 2021, pp. 21–30. [CCF-A]
• [ASC] Tingting Liang， Xuan Sheng， Li Zhou， Youhuizi Li， Honghao Gao，Yuyu Yin，Liang Chen, “Mobile app recommendation via heterogeneous graph neural network in edge computing”, Applied Soft Computing, May, 2021, Vol 103, pp. 107162.
• [ICSE] Jintang Li, Kun Xu, Liang Chen*, Zibin Zheng and Xiao Liu, “GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software”, 43rd International Conference on Software Engineering, demo track, Virtual, 2021, pp. 13-16, doi: 10.1109/ICSE-Companion52605.2021.00024. [CCF-A]
• [WWW] Yu Zheng, Chen Gao, Liang Chen, Yong Li, Depeng Jin, “Diversified Recommendation Through Similarity-Guided Graph Neural Networks”, 30th The Web Conference, Slovenia, April 2021, pp.401–412.[CCF-A]
• [ICDE] Tao Xie, Yangjun Xu, Liang Chen*, Yang Liu, and Zibin Zheng, “Sequential Recommendation on Dynamic Heterogeneous Information Network”, IEEE 37th International Conference on Data Engineering, Poster, Chania, Greece, 2021, pp. 2105-2110. [CCF-A]
• [WSDM] Yuanzhen Xie, Zijing Ou, Liang Chen*, Yang Liu, Kun Xu, Carl Yang and Zibin Zheng, “Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network”, 14th ACM International Conference on Web Search and Data Mining, Israel, March 8 - 12, 2021, pp.184-192.
• [AAAI] Kai Wang, Zhene Zou, Qilin Deng, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui, “Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation”, 35th AAAI Conference on Artificial Intelligence, Vol 35, Issue 5, pp.4427-4435.[CCF-A]
• [TOIT] Liang Chen, Jiaying Peng, Yang Liu, Jintang Li, Fenfang Xie, Zibin Zheng*, “Phishing Scams Detection in Ethereum Transaction Network”, ACM Transactions on Internet Technology, Jan, 2021, Vol 21, Issue 1, pp. 10:1-10:16. [Data]
  [SCI Impact Factor=3.135]
• [KBS] Fenfang Xie, Angyu Zheng, Liang Chen*, and Zibin Zheng, “Attentive Meta-graph Embedding for Item Recommendation in Heterogeneous Information Networks”, Knowledge-based Systems, Jan, 2021, Vol 211, pp. 106524.
  [SCI Impact Factor=8.038][中科院一区]
• [HBAI] Jintang Li, Zishan Gu, Qibiao Peng, Kun Xu, Liang Chen*, and Zibin Zheng, “Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective”, In International Workshop on Human Brain and Artificial Intelligence (pp. 87-101). Springer, Singapore.

2020

• [CIKM] Runze Wu, Hao Deng, Jianrong Tao, Changjie Fan, Qi Liu and Liang Chen, “Deep Behavior Tracing with Multi-level Temporality Preserved Embedding”, 29th ACM International Conference on Information and Knowledge Management, Applied Research Paper, Oct 19 - 23, 2020, pp. 2813-2820.
• [CIKM] Kai Wang, Hao Li, Linxia Gong, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen and Peng Cui, “Match Tracing: A Unified Framework for Real-time Win Prediction and Quantifiable Performance Evaluation”, 29th ACM International Conference on Information and Knowledge Management, Applied Research Paper, Oct 19 - 23, 2020, pp.2781-2788.
• [CIKM] Qilin Deng, Kai Wang, Minghao Zhao, Zhene Zou, Runze Wu, Jianrong Tao, Changjie Fan and Liang Chen, “Personalized Bundle Recommendation in Online Games”, 29th ACM International Conference on Information and Knowledge Management, Applied Research Paper, Oct 19 - 23, 2020, pp.2381-2388.
• [CIKM] Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen and Zibin Zheng, “Ensembled CTR Prediction via Knowledge Distillation”, 29th ACM International Conference on Information and Knowledge Management, Applied Research Paper, Oct 19 - 23, 2020, pp.2941-2958.
• [KDD] Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen and Tat-Seng Chua, “Interactive Path Reasoning on Graph for Conversational Recommendation”, KDD, Research Paper, San Diego, CA, US, August 23-27, 2020, pp.2073-2083. [CCF-A]
• [SIGIR] Yang Liu, Xianzhuo Xia, Liang Chen*, Xiangnan He, Carl Yang, Zibin Zheng, “Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines”, 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Research Paper, Xi’an, China, July 25-30, 2020, pp.419-428. [CCF-A]
• [SCC] Fenfang Xie, Zengxu Cao, Yangjun Xu, Liang Chen*, Zibin Zheng, “Graph Neural Network and Multi-view Learning based Mobile Application Recommendation in Heterogenous Graphs”, IEEE International Conference on Services Computing, Full Paper, Beijing, China, Oct 19-23, 2020, pp.100-107.
• [Arxiv] Liang Chen,Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng, “A Survey of Adversarial Learning on Graphs”, arxiv, March 2020.[PDF]
• [Access] Liang Chen, Yuanzhen Xie, Zibin Zheng, Huayou Zheng, Jingdun Xie, “Friend Recommendation based on Multi-social Graph Convolutional Network”, IEEE Access, Vol 8, pp. 43618-43629, 2020.
  [SCI Impact Factor=3.367]
• [DASFAA] Angyu Zheng, Liang Chen*, Fenfang Xie, Jianrong Tao, Changjie Fan and Zibin Zheng, “Keep You from Leaving: Churn Prediction in Online Games”, 25th International Conference on Database Systems for Advanced Applications, Jeju, South Korea, Sep 24-27, 2020, pp.263-279.
• [WWWJ] Liang Chen, Yongjian Ye, Fenfang Xie, Zibin Zheng, “Incorporating Geographical Location for Team Formation in Social Coding Sites”, World Wide Web Journal, Vol.23, 2020, pp. 153-174.
  [SCI Impact Factor=1.401]
• [TII] Bin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen, Yangdong Ye, “ATM: An Attentive Translation Model for Next-Item Recommendation”, IEEE Transactions on Industrial Informatics, Vol 16, Issue 3, pp.1448-1459, March, 2020.
  [SCI Impact Factor=10.215][中科院一区]
• [IOTJ] Huakun Huang, Shuxue Ding, Lingjun Zhao, Huawei Huang, Liang Chen, Honghao Gao, Syed Hassan Ahmed, “Real-Time Fault-Detection for IIoT Facilities using GBRBM-based DNN”, IEEE Internet of Things Journal, Vol.7, No.7, 2020, pp. 5713-5722.
  [SCI Impact Factor=9.471][中科院一区]
• [ECAI] Yang Liu, Jiaying Peng, Liang Chen*, Zibin Zheng, “Abstract Interpretation based Robustness Certification for Graph Convolutional Networks”, 24th European Conference on Artificial Intelligence, Full Paper, Santiago, Spain, June 8-12, 2020, pp.1309-1315.[PDF]
• [ECAI] Yangjun Xu, Liang Chen*, Fenfang Xie, Weibo Hu, Jieming Zhu, Chuan Chen, Zibin Zheng, “Directional Adversarial Training for Recommender Systems”, 24th European Conference on Artificial Intelligence, Full Paper, Santiago, Spain, June 8-12, 2020, pp.553-560. [PDF]
• [KAIS] Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S Yu, Jian Wu, “CAMAR: A Broad Learning based Context-Aware Recommender for Mobile Applications”, Knowledge and Information Systems, March 2020, Vol 62, pp.3291-3319.
  [SCI Impact Factor=2.822]
• [ETT] Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng, “Data Poisoning Attacks on Neighborhood-based Recommender Systems”, Transactions on Emerging Telecommunications Technologies, Vol 32, Issue 6, e3872.
  [SCI Impact Factor=2.638]

2019

• [CIKM] Xiongnan Jin, Byungkook Oh, Sanghak Lee, Dongho Lee, Kyong-Ho Lee, Liang Chen, “Learning Region Similarity over Spatial Knowledge Graphs with Hierarchical Types and Semantic Relations”, 28th ACM International Conference on Information and Knowledge Management, Full Paper, Beijing, China, Nov 3 - 7, 2019, pp.669-678.
• [IJCAI] Liang Chen, Yang Liu, Xiangnan He, Lianli Gao, and Zibin Zheng, “Matching User with Item Set: Collaborative Bundle Recommendation with Attention Network”, IEEE International Joint Conference on Artificial Intelligence, Main Track, Macao, China, 2019, pp.2095-2101.[CCF-A]
  [Code]
• [ICWS] Fenfang Xie, Shenghui Li, Liang Chen*, Yangjun Xu and Zibin Zheng, “Generative Adversarial Network Based Service Recommendation in Heterogeneous Information Network”, IEEE International Conference on Web Services, Research Track, Milan, Italy, 2019, pp.265-272.
• [KBS] Tingting Liang, Lei Zheng, Liang Chen, Yao Wan, Philip S. Yu, and Jian Wu, “Multi-view factorization machines for mobile app recommendation based on hierarchical attention”, Knowledge-based Systems, online publish, June ,2019.
  [SCI Impact Factor=8.038][中科院一区]
• [Electronics] Weiwei Zhuang, Liang Chen*, Chaoqun Hong, Yuxin Liang, Keshou Wu “FT-GAN: Face Transformation with Key Points Alignment for Pose-invariant Face Recognition”, Electronics, Vol.8, Issue.7, pp. 807-820, 2019.
  [SCI Impact Factor=3.022]
• [TSC] Tingting Liang, Liang Chen*, Jian Wu, Guandong Xu, Zhaohui Wu, “SMS: A Framework for Service Discovery by Incorporating Social Media Information”, IEEE Transactions on Services Computing, Vol 12, no. 3, pp. 384-397, 2019.
  [SCI Impact Factor=8.216]
• [Access] Yinglan Feng, Liang Chen*, Angyu Zheng, Cuiyun Gao, Zibin Zheng, “AC-Net: Assessing the Consistency of Description and Permission in Android Apps”, IEEE Access, Vol7, pp.57829-57842, 2019.
  [SCI Impact Factor=3.367]
• [Complexity] Liang Chen, Fenfang Xie, Zibin Zheng, Yaoming Wu, “Predicting Quality of Service via Leveraging Location Information”, Complexity, online publish, 2019.
  [SCI Impact Factor=2.833]
• [Access] Fenfang Xie, Liang Chen*, Dongding Lin, Zibin Zheng, Xiaola Lin, “Personalized Service Recommendation with Mashup Group Preference in Heterogeneous Information Network”, IEEE Access, Vol 7, pp.16115-16167, 2019.
  [SCI Impact Factor=3.367]

2018

• [CIKM] Liang Chen, Yang Liu, Zibin Zheng, and Philip Yu, “Heterogeneous Neural Attentive Factorization Machine for Rating Prediction”, 27th ACM International Conference on Information and Knowledge Management, Full Paper, Lingotto, Turin, Italy, Oct 22 - 26, 2018, pp.833-842.[Code]
• [ICSOC] Liang Chen, Angyu Zheng, Yinlan Feng, Fenfang Xie, and Zibin Zheng, “Software Service Recommendation Base on Collaborative Filtering Neural Network Model”, 16th International Conference on Services Oriented Computing, Full Paper, Hangzhou, China, Nov 12 - 15, 2018, pp.388-403.
• [ICSOC] Fengfang Xie, Liang Chen*, Yongjian Ye, Yang Liu, Zibin Zheng, and Xiaola Lin, “A Weighted Meta-graph Based Approach for Mobile Application Recommendation on Heterogeneous Information Networks”, 16th International Conference on Services Oriented Computing, Full Paper, Hangzhou, China, Nov 12 - 15, 2018, pp.404-420.
• [ICSOC] Lu Chen, Yuyu Yin, Yueshen Xu, Liang Chen, and Jian Wan, “Two-Phase Web Service QoS Prediction with Symmetric Restricted Boltzmann Machine”, 16th International Conference on Services Oriented Computing, Short Paper, Hangzhou, China, Nov 12 - 15, 2018, pp.592-600.
• [ICML] Shaoan Xie, Zibin Zheng, Liang Chen*, and Chuan Chen, “Learning Semantic Representations for Unsupervised Domain Adaptation”, 35th International Conference on Machine Learning, Full Paper, Stockholm, Sweden, July 10 - 17, 2018, pp.5423-5432. [CCF-A]
• [ICWS] Fengfang Xie, Liang Chen*, Yongjian Ye, Zibin Zheng, and Xiaola Lin, “Factorization Machine based Service Recommendation on Heterogeneous Information Networks”, 25th IEEE International Conference on Web Services, Research Track, San Francisco, USA, July 2 - 7, 2018, pp.115-122.
• [ICSE] Fenfang Xie, Liang Chen*, Dongding Lin, Chuan Chen, Zibin Zheng, and Xiaola Lin, “Group Preference based API Recommendation via Heterogeneous Information Network”, The 40th International Conference on Software Engineering, Gothenburg, Sweden, May 27 - June 3, 2018, pp. 362-363.[CCF-A]
• [NeuroC] Yao Wan, Guandong Xu, Liang Chen, Zhou Zhao, and Jian Wu, “Exploiting cross-source knowledge for warming up community question answering services”, NeuroComputing, vol.320, 2018, pp.25-34.
  [SCI Impact Factor=5.719]
• [KBS] Hongzhi Yin, Weiqing Wang, Liang Chen, Xingzhong Du, Quoc Viet Hung Nguyen, and Zi Huang, “Mobi-SAGE-RS: A sparse additive generative model-based mobile application recommender system”, Knowledge-based Systems, vol.157, 2018, pp.68-80.
  [SCI Impact Factor=8.038][中科院一区]
• [TCAS] Wendi Ren, Jiajing Wu, Xi Zhang, Rong Lai, Liang Chen, “A stochastic Model of Cascading Failure Dynamics in Communication Networks”, IEEE Transactions on Circuits and Systems II, Vol 65, No 5, pp. 632-636, 2018.
  [SCI Impact Factor=3.605]
• [WWWJ] Yao Wan, Liang Chen, Guandong Xu, Zhou Zhao, Jie Tang, Jian Wu, “SCSMiner: mining social coding sites for software developer recommendation with relevance propagation”, World Wide Web Journal, Vol21, Issue 6, pp.1523-1543, 2018.
  [SCI Impact Factor=1.401]

2017

• [ICDM] Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu, “A Broad Learning Approach for Context-Aware Mobile Application Recommendation”, The 17th International Conference on Data Mining, New Orleans, USA, Nov 18 - 21, 2017, pp.955-960.
• [ICSOC] Yaoming Wu, Fenfang Xie, Liang Chen, Chuan Chen, Zibin Zheng, “An Embedding based Factorization Machine Approach for Web Service QoS Prediction”, 15th International Conference on Services Oriented Computing, Full Paper, Malaga, Spain, Nov 13 - 16, 2017, pp.272-286.
  [accepted rate = 16%]
• [ICSOC] Yiwen Zhang, Xiaofei Ai, Qiang He, Xuyun Zhang, Wanchun Dou, Feifei Chen, Liang Chen, Yun Yang, “Personalized Quality Centric Service Recommendation”, 15th International Conference on Services Oriented Computing, Full Paper, Malaga, Spain, Nov 13 - 16, 2017, pp.528-544.
  [accepted rate = 16%]
• [ICWS] Tingting Liang, Liang Chen, Xingde Ying, Philip S. Yu, Jian Wu, and Zibin Zheng, “Mobile Application Rating Prediction via Feature-Oriented Matrix Factorization”, 24th International Conference on Web Services, Research Track, Honolulu, Hawaii, USA, June 25 - June 30, 2017, pp.261-268.
  [accepted rate = 21%]
• [ICDE] Hongzhi Yin, Liang Chen, Weiqing Wang, Xingzhong Du, Quoc Viet Hung Nguyen, Xiaofang Zhou, “Mobi-SAGE: A Sparse Additive Generative Model for Mobile App Recommendation”, 33rd International Conference on Data Engineering, San Diego, California, USA, April 19 - 22, 2017, pp. 75-78.[CCF-A]
• [PAKDD] Yuqiang Han, Yao Wan, Liang Chen, Guandong Xu, and Jian Wu, “Exploiting Geographical Location for Team Formation in Social Coding Sites”, 21th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Long Presentation Paper, Jeju, South Korea, May 23 - 26, 2017, pp.499-510.
  [accepted rate = 9.8%]
• [JWSR] Li Kuang, Gaofeng Cao,Liang Chen*, “Extracting Core Users Based on Features of Users and Their Relationships in Recommender Systems”, International Journal of Web Service Research, Volume 14, Issue 2, 2017, pp.1-23.
  [SCI indexed]

2016

• [WISE] Liang Chen, Haochao Ying, Qibo Qiu, Jian Wu, Hai Dong, and Athman Bouguettaya, “Temporal Pattern based QoS Prediction”, 17th International Conference on Web Information Systems Engineering, Full Paper, Shanghai, China, Nov 7 - 10, 2016, pp.223-237.
  [accepted rate = 16%]
• [ICSOC] Tingting Liang, Liang Chen, Jian Wu, Hai Dong, and Athman Bouguettaya, “Meta-Path based Service Recommendation in Heterogeneous Information Networks”, 14th International Conference on Services Oriented Computing, Full Paper, Alberta, Canada, Oct 10 - 13, 2016, pp.371-386. Best Paper & Best Student Paper Nomination （Top 5）
  [accepted rate = 21%]
• [ICSOC] Wei Gao, Liang Chen, Jian Wu, Hai Dong, and Athman Bouguettaya, “Personalized API Recommendation via Implicit Preference Modeling”, 14th International Conference on Services Oriented Computing, Short Paper, Alberta, Canada, Oct 10 - 13, 2016, pp.646-653.
  [accepted rate = 37%]
• [ICSOC] Bing Huang, Athman Bouguettaya, Hai Dong, and Liang Chen, “Service Mining for Internet of Things”, 14th International Conference on Services Oriented Computing, Short Paper, Alberta, Canada, Oct 10 - 13, 2016, pp.566-574.
  [accepted rate = 37%]
• [ICWS] Tingting Liang, Liang Chen, Jian Wu, and Athman Bouguettaya, “Exploiting Heterogeneous Information for Tag Recommendation in API Management”, 23rd International Conference on Web Services, Application Track, San Francisco, USA, June 27 - July 2, 2016, pp.436-443.
  [accepted rate = 26%]
• [ICWS] Wei Gao, Liang Chen, Jian Wu, and Athman Bouguettaya, “Joint Modeling Users, Services, Mashups and Topics for Service Recommendation”, 23rd International Conference on Web Services, Application Track, San Francisco, USA, June 27 - July 2, 2016, pp.260-267.
  [accepted rate = 26%]
• [ICWS] Ying Yin, Liang Chen, He Li, Xue Wang, and Bing Zhang, “An Efficient and Effictive Overlapping Communities Discovery based on Agglomerative Graph”, 23rd International Conference on Web Services, Short Paper, San Francisco, USA, June 27 - July 2, 2016, pp.708-711.
• [ICSE] Haochao Ying, Liang Chen, Tingting Liang, and Jian Wu, “Leveraging Expertise and Authority for Pull-Request Reviewer Recommendation in Github”, 38th International Conference on Software Engineering, 3rd Workshop on CrowdSourcing in Software Engineering, Austin, TX, USA, May 14 - 22, 2016, pp.29-35. [CCF-A]
• [WWW] Haochao Ying, Liang Chen, Yuwen Xiong, and Jian Wu, “PGRank: Personalized Geographical Ranking for Point-of-Interest Recommendation”, 25th World Wide Web Conference, Poster Paper, Montreal, Canada, April 11 - 15, 2016, pp.137-138. [CCF-A]
• [PAKDD] Haochao Ying, Liang Chen, Yuwen Xiong, and Jian Wu, “Collaborative Deep Ranking: a Hybrid Pair-wise Recommendation Algorithm with Implicit Feedback”, 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Regular Paper, Auckland, New Zealand, April 19 - 22, 2016, pp.555-567.
• [PAKDD] Yao Wan, Liang Chen, Qi Yu, Tingting Liang, and Jian Wu, “Incorporating Heterogeneous Information for Mashup Discovery with Consistent Regularization”, 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Regular Paper, Auckland, New Zealand, April 19 - 22, 2016, pp.436-448.
• [CACM] Athman Bouguettaya, Munindar Singh, Michael Huhns, Quan Z. Sheng, Hai Dong, Qi Yu, Azadeh Ghari Neiat, Sajib Mistry, Boualem Benatallah, Brahim Medjahed, Mourad Ouzzani, Fabio Casati, Xumin Liu, Hongbing Wang, Dimitrios Georgakopoulos, Liang Chen, Surya Nepal, Zaki Malik, Abdelkarim Erradi, Yan Wang, Brian Blake, Schahram Dustdar, Frank Leymann, Michael Papazoglou, “A Service Computing Manifesto: The Next Ten Years”, Communications of the ACM, Volume 60, Issue 4, 2016, pp.64-72.
  [SCI Impact Factor=4.654]
• [TSC] Zhaohui Wu, Jianwei Yin,Shuiguang Deng, Jian Wu, Ying Li, Liang Chen,”Modern Service Industry and Crossover Services: Development and Trends in China”, . IEEE Transactions on Services Computing, Volume 9, Issue 5, 2016, pp.664-671.
  [SCI Impact Factor=8.216]

2015

• [ICDM] Tingting Liang, Liang Chen, Haochao Ying, Zibin Zheng, Jian Wu, “Crowdsourcing based API Search via Leveraging Twitter Lists Information”, The 15th International Conference on Data Mining, PhD. Forum, Regular Paper, Atlantic City, NJ, USA, Nov 14 - 17, 2015, pp.1540-1547.
  [accepted rate = 28%]
• [ICSOC] Tingting Liang, Liang Chen, Zhining Xie, Wei Yang, Jian Wu, “CASE: A Platform for Crowdsourcing based API Search”, The 13th International Conference on Service Oriented Computing, Demo Track, Goa, India, Nov 16 - 19, 2015, pp.482-485.
• [MS] Guangtai Liang, Lijun Mei, Shaochun Li, Liang Chen, “Exploiting Unique Characteristics of Mobile Backend Services to Recommend Right Ones”, The 4th International Conference on Mobile Services, New York, USA, June 27 - July 2, 2015, pp.464-467.
• [ICWS] Liang Chen, Qi Yu, Philip S. Yu, Jian Wu, “WS-HFS: A Heterogeneous Feature Selection Framework for Web Services Mining”, The 22nd International Conference on Web Services, Research Track, New York, USA, June 27 - July 2, 2015, pp.193-200.
  [accepted rate = 17.4%]
• [ICWS] Qi Yu, Hongbing Wang, Liang Chen, “Learning Sparse Functional Factors for Large-scale Service Clustering”, The 22nd International Conference on Web Services, Research Track, New York, USA, June 27 - July 2, 2015, pp.201-208.
  [accepted rate = 17.4%]
• [ICWS] Wei Gao, Liang Chen, Jian Wu, Honghao Gao, “Mainfold-Learning based API Recommendation for Mashup Creation”, The 22nd International Conference on Web Services, Application Track, New York, USA, June 27 - July 2, 2015, pp.432-439.
  [accepted rate = 21.9%]
• [ICWS] Yao Wan, Liang Chen, Jian Wu, Qi Yu, “Time-aware API Popularity Prediction via Heterogeneous Features”, The 22nd International Conference on Web Services, Application Track, New York, USA, June 27 - July 2, 2015, pp.424-431.
  [accepted rate = 21.9%]
• [WSDM] Shuangling Bai, Liang Chen, Jian Wu, “Heterogeneous Information Network based Ranking and Clustering of Mobile Apps”, Scalable Data Analytica: Theory & Applications, in conjunction with 8th International Conference on Web Search and Data Mining, Shanghai, China, Feb. 2-6, 2015.
  [accepted rate = 20%]

2014

• [SOCA] Tingting Liang, Liang Chen, Haochao Ying, Jian Wu, “Co-clustering WSDL Documents to Bootstrap Service Discovery”, The 7th International Conference on Service Oriented Computing and Applications, Matsue, Japan, Nov. 17-19, 2014, pp. 215-222.
  [accepted rate = 26%]
• [PAKDD] Liang Chen, Yilun Wang, Lichuan Ji, Tingting Liang, Jian Wu, “Data Augmented Maximum Margin Matrix Factorization for Flickr Group Recommendation”, The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Tainan, Taiwan, May 13-16, 2014, pp. 473-484.
  [accepted rate = 10.8%]
• [TSC] Liang Chen, Jian Wu, Hengyi Jian, Hongbo Deng, Zhaohui Wu, “Instant Recommendation for Web Services Composition”, IEEE Transactions on Service Computing, Volume 7, Issue 4, 2014, pp.586-598.
  [SCI Impact Factor=8.13]
• [KAIS] Liang Chen, Jian Wu, Zibin Zheng, Yanan Xie, Yilun Wang, Michael R. Lyu, Zhaohui Wu, “Modeling and Exploring Tag Relevance for Web Service Mining”, International Journal of Knowledge and Information Systems, Volume 39, Issue 1, 2014, pp.153-173.
  [SCI Impact Factor=2.822]
• [KAIS] Jian Wu, Liang Chen*, Zibin Zheng, Michael R. Lyu, Zhaohui Wu, “Clustering Web Services to Facilitate Service Discovery”, International Journal of Knowledge and Information Systems, Volume 38, Issue 1, 2014, pp. 207-229.
  [SCI Impact Factor=2.822]
• [IJWGS] Jian Wu, Liang Chen*, Yanan Xie, Lichuan Ji, Zhaohui Wu, “Modeling and Exploring Historical Records to Facilitate Service Composition”, International Journal of Web and Grid Services, Volume 10, Issue 1, 2014, pp. 54-79.
  [SCI Impact Factor=7.135]
• [JWSR] Mingdong Tang, Zibin Zheng, Liang Chen, Jianxun Liu, Buqing Cao, Zhengguang You, “A Trust-aware Search Engine for Complex Service Computing”, International Journal of Web Services Research, Volume 11, Issue 1, 2014, pp. 57-75.
  [SCI indexed]

2013

• [SOCA] Liang Chen, Yipeng Feng, Jian Wu, “Collaborative QoS Prediction via Feedback-based Trust Model”, The 6th International Conference on Service Oriented Computing and Applications, Kauai, Hawaii, USA, Dec 16-18, 2013, pp. 206-213.
  [accepted rate = 20.3%]
• [SOCA] Tingting Liang, Lichuan Ji, Liang Chen, Jian Wu, “Collaborative QoS Prediction via Matrix Factorization and Topic Model”, The 6th International Conference on Service Oriented Computing and Applications, Kauai, Hawaii, USA, Dec 16-18, 2013, pp. 282-289.
  [accepted rate = 20.3%]
• [MIDDLEWARE] Chen Shen, Yao Zhao, Liang Chen, “Galaxie: A P2P Based EDSOA Platform for Cloud Services”, ACM/IFIP/USENIX International Middleware Conference, Demo Track, Beijing, China, Dec 9-13, 2013, pp. 9-12.
• [ICSOC] Liang Chen, Yilun Wang, Qi Yu, Zibin Zheng, Jian Wu, “WT-LDA: User Tagging Augmented LDA for Web Service Clustering”, 11st International Conference on Service Oriented Computing, Berlin, Germany, Dec 2 - 5, 2013, pp. 162-176.
  [accepted rate = 13%]
• [CIKM] Yilun Wang, Liang Chen, Jian Wu, “Content-boosted Maximum Margin Matrix Factorization for Flickr Group Recommendation”, Data-driven User Behavioral Modelling and Mining from Social Media, in conjunciton with 22nd ACM International Conference on Information and Knowledge Management, San Francisco, USA, Oct 27- Nov 1, 2013, pp. 13-16.
• [CIKM] Yanan Xie, Liang Chen, Kunyang Jia, Lichuan Ji, Jian Wu, “iNewsBox: Modeling and Exploiting Implicit Feedback for Building Personalized News Radio”, 22nd ACM International Conference on Information and Knowledge Management, Demo Track, San Francisco, USA, Oct 27- Nov 1, 2013, pp. 2485-2488.
• [BIGDATA] Li Kuang, Liang Chen, Yanan Xie, Jian Wu, “Full Recognition of Massive Commodities Based on Property Set”, IEEE International Congress on Big Data, Santa Clara Marriott, USA, June 27- July 2, 2013, pp. 294-301.
• [PAKDD] Panpan Han, Liang Chen, Jian Wu, “A Semantic-based Dual Caching System for Nomadic Web Service”, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, workshop, Gold Coast, Australia, April 14-17, 2013, pp. 511-521.
• [PAKDD] Hanze Xu, Yanan Xie, Dinglong Duan, Liang Chen, Jian Wu, “FTCRank: Ranking Components for Building Highly Reliable Cloud Applications”, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, workshop, Gold Coast, Australia, April 14-17, 2013, pp. 522-532.
• [WWWJ] Jian Wu, Liang Chen*, Qi Yu, Panpan Han, Zhaohui Wu, “Trust-aware Media Recommendation in Heterogeneous Social Networks”, World Wide Web Journal, Volume 18, Issue 1, 2013, pp. 139-157.
  [SCI Impact Factor=1.401]
• [CLUS] Jian Wu, Liang Chen*, Qi Yu, Li Kuang, Yilun Wang, Zhaohui Wu, “Selecting Skyline Services for QoS-aware Composition by Upgrading MapReduce Paradigm”, Cluster Computing, Springer, Volume 16, Issue 4, 2013, pp. 693-706.
  [SCI Impact Factor=1.809]
• [TSMC] Jian Wu, Liang Chen*, Yipeng Feng, Zibin Zheng, Mengchu Zhou, Zhaohui Wu, “Predicting Quality of Service for Selection by Neighborhood-based Collaborative Filtering”, IEEE Transactions on System, Man, and Cybernetics, Part A, Volume 43, Issue 2, 2013, pp. 428-439.
  [SCI Impact Factor= 6.663]

2012

• [ICSOC] Liang Chen, Zibin Zheng, Yipeng Feng, Jian Wu, Michael R. Lyu, “WSTRank: Ranking Tags to Facilitate Web Service Mining”, 10th International Conference on Service Oriented Computing, Shanghai, China, November 12-15, 2012, pp. 574-581.
  [accepted rate = 29%]
• [ICWS] Liang Chen, Hengyi Jian, Jian Wu, “WSCRec: Utilizing Historical Information to Facilitate Web Service Composition”, 10th International Conference on Web Services, Honolulu Hawii, USA, June 24-29, 2012.
  [accepted rate = 17%]
• [IPDPS] Liang Chen, Li Kuang, Jian Wu, “MapReduce based skyline services selection for QoS-aware composition”, IEEE 26th International Parallel and Distributed Processing Symposium, workshop, Shanghai, China, May 21-25, 2012, pp. 2035-2042.
• [IPDPS] Liang Chen, Kai Hwang, Jian Wu, “MapReduce Skyline Query Processing with a New Angular Partitioning Approach”, IEEE 26th International Parallel and Distributed Processing Symposium, workshop, Shanghai, China, May 21-25, 2012, pp. 2262-2270.
• [WWW] Jian Wu, Liang Chen, Yanan Xie, Zibin Zheng, “Titan: A System for Effective Web Service Discovery”, 21th International World Wide Web Conference, Demo Track, Lyon, France, April 16-20, 2012, pp. 441-444. [CCF-A]
  [accepted rate = 20%]
• [JWSR] Jian Wu, Liang Chen*, Hengyi Jian, Zhaohui Wu, “Composite Service Recommendation Based on Bayes Theorem”, International Journal of Web Services Research, Volumn 9, Issue 2, 2012, pp. 69-93.
  [SCI indexed]

2011

• [ICSOC] Liang Chen, Liukai Hu, Zibin Zheng, Jian Wu, “WTCluster: Utilizing Tags for Web Services Clustering”, 9th International Conference on Service Oriented Computing, Paphos, Cyprus, December 5-8, 2011, pp. 204-218.
  [accepted rate = 16%]
• [SCC] Liang Chen, Yipeng Feng, Jian Wu, Zibin Zheng, “An Enhanced QoS Prediction Approach for Service Selection”, 8th International Conference on Service Computing [SCC], Washington DC, USA, July 5-10, 2011.
  [accepted rate = 26%]
• [SCC] Limin Pan, Liang Chen, Jian Hui, Jian Wu, “QoS-based distributed service selection in large-scale web services”, 8th International Conference on Service Computing, Washington DC, USA, July 5-10, 2011, pp. 725-726.
  [accepted rate = 26%]
• [SCC] Yin Ma, Liang Chen, Jian Hui, Jian Wu, “CBBCM: Clustering Based Automatic Service Composition”, 8th International Conference on Service Computing, Washington DC, USA, July 5-10, 2011, pp. 354-361.
  [accepted rate = 26%]
• [CSSS] Limin Pan, Liang Chen, Jian Wu, “Skyline Web Service Selection with MapReduce”, International Conference on Computer Science and Service System, Nanjin, China, June 27-29, 2011, pp. 739-743.

2010

• [ICWS] Liang Chen, Jian Wu, Ru Jia, “Recommendation on Uncertain Services”, 8th International Conference on Web Services, Miami, USA, July 5-10, 2010. [accepted rate = 17.6%]
• [SERVICES] Liang Chen, Jian Wu, Shuiguang Deng, Ying Li, “Service Recommendation: Similarity-based Representative Skyline”, 6th IEEE World Congress on Services, Miami, USA, July 5-10, 2010, pp. 360-366.
• [CJC] Jian Wu, Liang Chen*, Shuiguang Deng, Ying Li and Li Kuang, “QoS-Skyline Based Dynamic Service Selection”, Chinese Journal of Computers (计算机学报), Volume 33, Issue 11, 2010, pp. 2136-2146.