Graduate and Undergraduate Students from the Faculty of Information Science and Engineering Jointly Publish Articles in CCF A-level Conferences
Publishing time：2022-03-25
Academic paper "Scalable Motif Counting for Large-scale Temporal Graph" (面向大规模时序图的可扩展Motif计数), co-authored by Gao Zhongqiang, a master's student majoring in electronic information, and Cheng Chuanqi, an undergraduate student majoring in computer science and technology from the Faculty of Information Science and Engineering, has been accepted by the A-level conference ICDE2022 sponsored by the China Computer Federation (CCF) on March 24, 2022. The paper was completed under the guidance of Associate Professor Yu Yanwei from the School of Computer Science and Technology. The team had previously published papers in top international conferences such as WWW 2021 (CCF A-level conference) in the field of Internet and ICDM 2021 (CCF B-level conference) in the field of data mining. This achievement marks another significant breakthrough for the research team in the field of data engineering and is also the first time that an undergraduate from Ocean University of China's School of Computer Science and Technology has published a paper in a CCF A-level international conference, which actively and effectively explores the innovative talent training mechanism for undergraduate students at Ocean University of China.
Network motifs are an important type of frequent subgraphs that can effectively capture high-order local structures in networks. They have been widely used in network representation learning and various network mining applications. For example, in the e-commerce network, these frequent network motifs can effectively model various interactions between users and commodities; in social network analysis, motifs mined from large dynamic networks are often used to understand how human communication unfolds. How to effectively mine these subgraph structures has become a bottleneck problem for large-scale temporal graph mining. The research proposes an efficient parallel mining framework model that can effectively mine and count various types of temporal motifs instances from large-scale temporal graphs, effectively solving this bottleneck problem.
ICDE (IEEE International Conference on Data Engineering) is a flagship conference hosted by the Institute of Electrical and Electronics Engineers (IEEE) and is one of the three top international conferences in the field of data management and databases, along with SIGMOD and VLDB. It has been selected as a CCF recommended A-level international academic conference and enjoys a high reputation and wide academic influence internationally. ICDE has extremely high requirements for paper quality, with an average acceptance rate of about 19.1%.
