- Graph algorithms
- Heteogeneous graphs
- Distributed computing
- Yue Wang, Ruiqi Xu, Zonghao Feng, Yulin Che, Lei Chen, Qiong Luo, Rui Mao: DISK: A Distributed Framework for Single-Source SimRank with Accuracy Guarantee.
The 47th International Conference on Very Large Data Bases, 2021.
- Jingzhi Fang, Yanyan Shen, Yue Wang, Lei Chen: Optimizing DNN Computation Graph using Graph Substitutions. The 46th International Conference on Very Large Data Bases, 2020.
- Alexander Zhou, Yue Wang*, Lei Chen: Finding Large Diverse Communities on Networks: The Edge Maximum k*-Partite Clique. The 46th International Conference on Very Large Data Bases, 2020.
- Xun Jian, Yue Wang*, Lei Chen: Effective and Efficient Relational Community Detection and Search in Large Dynamic Heterogeneous Information Networks. The 46th International Conference on Very Large Data Bases, 2020.
- Yulin Che, Zhuohang Lai, Shixuan Sun, Yue Wang, Qiong Luo: Accelerating Truss Decomposition on Heterogeneous Processors. The 46th International Conference on Very Large Data Bases, 2020.
- Xun Jian, Yue Wang, Xiayu Lei, Libin Zheng, Lei Chen：SPARQL Rewriting: Towards Desired Results ACM Conference on Management of Data（SIGMOD 2020）, June 14-19, 2020, Portland Oregon, USA
- Xun Jian, Yue Wang, Xiayu Lei, Yanyan Shen, Lei Chen: DDSL: Efficient Subgraph Listing on Distributed and Dynamic Graphs. (Short Paper) The 25th International Conference on Database Systems for Advanced Applications, May 21-24, 2020, Jeju, South Korea.
- Zijian Li, Wenhao Zheng, Xueling Lin, Ziyuan Zhao, Zhe Wang, Yue Wang, Xun Jian, Lei Chen, Qiang Yan, Tiezheng Mao：TransN: Heterogeneous Network Representation Learning by Translating Node Embeddings IEEE International Conference on Data Engineering（ICDE 2020）, April 20-24, 2020, Dallas, Texas, USA
- Yue Wang, Zhe Wang, Ziyuan Zhao, Zijian Li, Xun Jian, Lei Chen, Jianchun Song：HowSim: A General and Effective Similarity Measure on Heterogeneous Information NetworksIEEE International Conference on Data Engineering（ICDE 2020）, April 20-24, 2020, Dallas, Texas, USA
- Yulin Che, Zhuohang Lai, Shixuan Sun, Qiong Luo, Yue Wang: Accelerating All-Edge Common Neighbor Counting on Three Processors. The 48th International Conference on Parallel Processing, August 5-8, 2019, Kyoto Research Park, Kyoto, Japan.
- Zijian Li, Lei Chen, Yue Wang: G*-Tree: An Efficient Spatial Index on Road Networks. The 35th International Conference on Data Engineering, 8-12 April 2019, Macau SAR, China.
- Yue Wang, Xiang Lian, Lei Chen: Efficient SimRank Tracking in Dynamic Graphs. The 34th International Conference on Data Engineering, 16-19 April 2018, Paris, France.
- Yue Wang, Zhe Wang, Ziyuan Zhao, Zijian Li, Xun Jian, Hao Xin, Lei Chen, Jianchun Song, Zhenhong Chen, Meng Zhao: Effective Similarity Search on Heterogeneous Networks: A Meta-path Free Approach. IEEE Transactions on Knowledge and Data Engineering, 2020.
- Wenfei Fan, Kun He, Qian Li, Yue Wang: Graph Algorithms: Parallelization and Scalability. SCIENCE CHINA Information Sciences, 2020.
- Yue Wang, Zonghao Feng, Lei Chen, Zijian Li, Xun Jian, Qiong Luo：Efficient Similarity Search for Sets over Graphs IEEE Transactions on Knowledge and Data Engineering（TKDE 2019）
- Yue Wang, Yulin Che, Xiang Lian, Lei Chen, Qiong Luo：Fast and Accurate SimRank Computation via Forward Local Push and Its Parallelizatio. IEEE Transactions on Knowledge and Data Engineering（TKDE 2020）
- Yue Wang, Lei Chen, Yulin Che, Qiong Luo: Accelerating Pairwise SimRank Estimation over Static and Dynamic Graphs. The VLDB Journal, 28(1): 99-122, 2019.
- Yue Wang, Xun Jian, Zhenhua Yang, Jia Li: Query Optimal k-Plex Based Community in Graphs. Data Science and Engineering, 2(4): 257-273, 2017.
- Postgraduate Scholarship, CSE Dept., HKUST, Annually (2014 – 2019).
- Outstanding Graduate from Beihang University, BUAA, Jun 2013.
RML (Logic Rules and Machine Learning) is a system that mainly builds a high data availability cloud platform. Under the guidance of the self-developed data quality foundational theory, RML uses the combination of rules and AI under a unified logic framework to solve data consistency, timeliness, and the same problem of accuracy, completeness, and substance. The system is oriented to centralized/distributed data, relational/graph data to create a one-stop solution for data and knowledge collection, quality evaluation, data analysis, data error checking, entity recognition, data repair, and data fusion. RML takes advantage of China’s data scale to form a positive cycle of two-way interaction between data and the platform and accelerate the high-quality conversion of data to digital intelligence. It promotes the high-quality application of data production factors in various industries, consolidates the digital economy’s infrastructure, and leads the development of global data availability.