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Introduction

Collaborative Intelligence Technology Lab (CIT) is affiliated to the Network and Services Computing Institute, Shanghai Jiao Tong University. The director of the laboratory is Professor Cao Jian. At present, the laboratory has 2 teachers, 12 doctoral students, 9 master students. The main research domains include but are not limited to:

Services Computing ：With the development of software technology and Internet technology, many business functions are delivered via Internet in the mode of software service. As a result, services on the Internet have formed a service ecosystem. How to make use of multiple services in the service space to provide users with personalized and high-quality services has practical meanings. Laboratory research focuses on: (1) Service process management; (2) Personalized services; (3) Intelligent services.
Network Computing ：Network computing mode has become the mainstream computing one, grid computing, pervasive computing, cloud computing and other forms of computing are essentially network computing. This laboratory focuses on the collaborative mechanism of widely distributed heterogeneous autonomous computing resources in network computing. Specific research domains are as follows: (1) Cloud workflow modeling; (2) Cloud market modeling; (3) Hybrid cloud modeling.
Intelligent Data Analysis ：With the promotion of the concept of big data, the value of data becomes more and more important. To make data valuable, however, whether it is "big" or "small", the core issue is how to analyze it in depth, based on understanding the data. In recent years, the laboratory has carried on the key research in this direction, and has carried on the extensive and thorough cooperation with many enterprises. The specific research domains are as follows: (1) Personalized recommendation; (2) Distributed system intelligent monitoring; (3) Decision support in the medical field; (4) Personalized tourism service; (5) Intelligent analysis of enterprise data.

Students who are interested in doing research in these fields are welcome to join the lab! Welcome to contact Professor Cao Jian and Shiyou Qian!

Members

Jian Cao

Shiyou Qian

Yang Gu

Qin Hua

Bohan Gu

Wei Guan

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Publications

In recent years, the laboratory has achieved a lot in important international journals (including TKDE, TKDD, TOIS, WWWJ, TOMM, etc.) and important international conferences (such as AAAI, IJCAI, IEEE ICWS, WSDM, ICSOC, DASFAA, etc.), including 66 journal papers, 156 conference papers, and 0 patent authorization. The partial list is as follows:

Journal

Nengjun Zhu, Jian Cao*, Xinjiang Lu, Hui Xiong: Learning a Hierarchical Intent Model for Next-Item Recommendation. ACM Trans. Inf. Syst. 40(2): 38:1-38:28 (2022)

Nengjun Zhu, Jian Cao*, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, and Hui Xiong. 2022. Predicting a Person’s Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network. ACM Trans. Knowl. Discov. Data 16, 6, Article 116 (December 2022), 23 pages. https://doi.org/10.1145/3529091

X. Wang, J. Cao* and R. Buyya, "Adaptive Cloud Bundle Provisioning and Multi-Workflow Scheduling via Coalition Reinforcement Learning," in IEEE Transactions on Computers, 2022, doi: 10.1109/TC.2022.3191733.

Shiyou Qian, Bin Chen, Jian Cao*, Guangtao Xue, Jiadi Yu, Yanmin Zhu, Minglu Li, Tao Zhang, Detecting Taxi Trajectory Anomaly based on Spatio-Temporal Laws, IEEE Intelligent Transportation Systems, vol. 23, no. 7, pp. 6883-6894, July 2022, doi: 10.1109/TITS.2021.3063199.

Qi Gu, Jian Cao*, Yancheng Liu, CSBR: A Compositional Semantics-based Service Bundle Recommendation Approach for Mashup Development, IEEE Transactions on Service Computing, DOI: 10.1109/TSC.2021.3085491

Tianchen Ding, Shiyou Qian, Jian Cao, Guangtao Xue, Yanmin Zhu, Jiadi Yu, Minglu Li: MO-Tree: An Efficient Forwarding Engine for Spatiotemporal-Aware Pub/Sub Systems. IEEE Trans. Parallel Distributed Syst. 32(4): 855-866 (2021)

Jian Cao*, Tingjie Jia, Shiyou Qian, Haiyan Zhao, Jie Wang: CBPCS: A Cache-block-based Service Process Caching Strategy to Accelerate the Execution of Service Processes. ACM Trans. Web 15(1): 1:1-1:29 (2021)

Nengjun Zhu, Jian Cao, Kunwei Shen, Xiaosong Chen, and Siji Zhu: A Decision Support System with Intelligent Recommendation for Multi-disciplinary Medical Treatment [J]. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 16, no. 1s (2020): 1-23.

Wenjuan Li, Jian Cao, Shiyou Qian, Rajkumar Buyya: TSLAM: A Trust-enabled Self-Learning Agent Model for Service Matching in the Cloud Market [J]. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 2019, 13(4): 16:1-41

Shiyou Qian, Jian Cao, Weichao Mao, Yanmin Zhu, Jiadi Yu, Minglu Li, Jie Wang. A fast and anti-matchability matching algorithm for content-based publish/subscribe systems [J]. Computer Networks, 2019, 149(11): 213-225

Chenyang Liu, Jian Cao, Shanshan Feng: Leveraging Kernel-Incorporated Matrix Factorization for App Recommendation [J]. ACM Transactions on Knowledge Discovery From Data (TKDD), 2019, 13(3):1-27

Liang Hu, Qingkui Chen, Haiyan Zhao, Songlei Jian, Longbing Cao, Jian Cao. Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context [J]. IEEE Intelligent Systems, 2018, 33(6): 57-67

Conference

Yao Wu, Jian Cao*, Guandong Xu, Yudong Tan: TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers. SIGIR 2021: 1013-1022

Qi Q., Cao J.*, Liu Y. (2021) API-PROGRAM: An API Package Recommendation Model Based on the Graph Representation Learning Method. In: Hacid H., Kao O., Mecella M., Moha N., Paik H. (eds) Service-Oriented Computing. ICSOC 2021.

Nengjun Zhu and Jian Cao: Enhancing Cross-domain Recommendation through Preference Structure Information Sharing [C]// IEEE International Conference on Web Services (ICWS). IEEE, 2020

Nengjun Zhu, Jian Cao, Yanchi Liu, Yang Yang, Haochao Ying, and Hui Xiong: Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation [C]// The 13th International Conference on Web Search and Data Mining (WSDM), pp. 807-815. 2020.

Jian Cao, Xiaofu Huang, Qing Qi: Selecting Publishing Points for the Optimal Sharing of Predictive Monitoring Information of a Service Process [C]// The 26th IEEE International Conference on Web Services (ICWS 2019), Milan, Italy, July 8-13, 2019: 368-372

Lanxuan Tong, Jian Cao, Qing Qi, Shiyou Qian: AIMS: A Predictive Web API Invocation Behavior Monitoring System [C]//The 26th IEEE International Conference on Web Services (ICWS 2019), Milan, Italy, July 8-13, 2019: 373-382

Shiyou Qian, Weichao Mao, Jian Cao, Frederic Le Mouel, Minglu Li: Adjusting Matching Algorithm to Adapt to Workload Fluctuations in Content-based Publish/Subscribe Systems [C]// 2019 IEEE International Conference on Computer Communications (INFOCOM 2019), Paris, France, 29 April - 2 May, 2019: 1936-1944

Yan Yao, Jian Cao, Zitai Ma: A Cost-Effective Deadline-Constrained Scheduling Strategy for a Hyperparameter Optimization Workflow for Machine Learning Algorithms [C]// The 16 th International Conference on Service-Oriented Computing (ICSOC 2018), HangZhou, China, November 12-15, 2018: 870-878

Jian Cao, Yuchang Xu, Huisi Ou, Yudong Tan, Quan-Wu Xiao: PFS: A Personalized Flight Recommendation Service via Cross-Domain Triadic Factorization [C]// The 25th IEEE International Conference on Web Services (ICWS 2018), San Francisco, USA, July 2 - 7, 2018: 249-256

Yuchang Xu, Jian Cao, Tao Liu, Yudong Tan, Quan-Wu Xiao: When to Invoke a Prediction Service? A Reinforcement Learning-Based Approach [C]//. The 25th IEEE International Conference on Web Services (ICWS 2018), San Francisco, USA, July 2 - 7, 2018: 315-318

Chenyang Liu, Jian Cao, Jing He: Leveraging Kernel Incorporated Matrix Factorization for Smartphone Application Recommendation [C]// The 22nd International Conference on Database Systems for Advanced Applications (DASFAA 2017), Suzhou, China, March 27-30, 2017: 459-474

Yiqun Hua, Jian Cao, Qi Gu, Yudong Tan: PD-TRP: A Service Composition Approach for the Personalized and Optimized Door-to-Door Travel Plan Recommendation [C]// 2017 IEEE International Conference on Web Services (ICWS 2017), Honolulu, HI, USA, June 25-30, 2017: 768-775

Yan Yao, Jian Cao, Yusheng Jiang: EWS: A Pattern Prediction-Based Elastic Workflow Service in the Cloud [C]// 2017 IEEE International Conference on Web Services (ICWS 2017), Honolulu, HI, USA, June 25-30, 2017: 784-791

Liang Hu, Longbing Cao, Shoujin Wang, Guandong Xu, Jian Cao, Zhiping Gu: Diversifying Personalized Recommendation with User-session Context [C]// The 26th International Joint Conference on Artificial Intelligence (IJCAI2017), Melbourne, Australia, August 19-25, 2017: 1858-1864

Zhenni Feng, Yanmin Zhu, Jian Cao: Modeling Air Travel Choice Behavior with Mixed Kernel Density Estimations [C]// The Tenth ACM International Conference on Web Search and Data Mining (WSDM2017), Cambridge, UK, February 6-10, 2017: 611-620

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Projects

We undertake a number of national, provincial and municipal key projects.

在研

上海市科委人工智能科技支撑专项课题（22DZ1100103），自动驾驶试验场数据质量保障方法与工具（2022.7-2024.6）

上海市科委人工智能科技支撑专项（21511104700），多智能体的动态重组机制及其在分布式态势感知与预测中的应用（2021.11-2024.10)

国家重点研发计划子课题（2019YFB1704405），事件驱动大规模服务调用、可靠性保障技术研究，（2019年12月至2022年11月）

国家自然科学基金项目，面向业务过程预测性监控的情境信息协同获取与模型学习（2021.1-2024.12）项目批准号：62072301

已结题

国家自然科学基金，61472253，基于社会化感知数据多层次学习的服务推荐，2015/01-2018/12

国家863计划，2001AA415310，基于Agent与工作流技术的面向实施的企业业务过程建模与评价环境，2001/10-2003/9

国家自然科学基金，61272438，分布式云工作流服务的自适应模型与机制， 2013/01-2016/12