The 1th International Workshop on Graph Data Management, Mining and Applications (GDMMA2025)

Workshop Aim and Scope

Graph data, with its powerful associative expression ability, has become the key to understanding complex systems and exploring potential value. Efficient management of graph data not only ensures data quality but also accelerates data access, providing a solid foundation for analysis. In-depth mining of graph data can reveal hidden relationships and patterns, providing strong support for prediction, decision-making, etc. With the rise of big data and AI technologies, the application of graph data is becoming increasingly widespread, and its management and mining capabilities have become the core elements driving innovation and enhancing competitiveness

The 1st International APWeb-WAIM Workshop on Graph Data Management, Mining and Applications (GDMMA 2025) will take place on August 28th-30th, 2025, Shenyang, China, in conjunction with APWeb-WAIM which is an annual international conference on Web and Big Data. The objective of GDMMA 2025 is to provide a dedicated forum to bring together researchers, practitioners and others to share and exchange ideas, practical development experiences and the latest research results on graph data management, mining and applications. GDMMA 2025 will provide an excellent opportunity for the researchers from academia and industry as well as practitioners to showcase the latest advances in this area and to discuss future research directions and challenges on graph data management,mining and applications.

Submission Guidelines

The workshop's scope includes all important aspects of information technology including storage, query processing, analytics and quality of graph data, especially for applications in fields. The topics of interest for GDMMA include, but are not limited to:

• AI for graph data management
• Advanced applications and tools for managing graph databases in different domains
• Compact (compressed) representation of graph data
• Estimating the selectivity of graph queries
• Graph mining
• Graph learning
• Graph data management for social network applications
• Graph data management of multimedia databases
• Graph data management of semantic web data
• Graph data management for geometrical applications
• Graph data management for business process management applications
• Graph query languages
• Graph question answering
• Indexing graph data
• Measuring graph similarity
• Storing graph data
• Supporting different types of graph queries

Paper Submission Guidelines:

https://cmt3.research.microsoft.com/APWebWAIM2025
Select the track: Workshop-GDMMA

Important Dates

*All deadlines are 23:59 Anywhere on Pacific time.

Organizers

• Workshop Chair
  Jun Pang (pangjun@wust.edu.cn) Wuhan University of Science and Technology, China
• Program Committee Members
  Kai Zhang (zhangkai@wust.edu.cn) Wuhan University of Science and Technology, China
  Xin Xu (xuxin@wust.edu.cn) Wuhan University of Science and Technology, China
  Minghe Yu (yuminghe@mail.neu.edu.cn) Northeastern University, China
  Jia Xu (xujia@gzhu.edu.cn) Guangzhou University, China
  Zhiqiong Wang (wangzq@bmie.neu.edu.cn) Northeastern University, China
  Tianyi Li (tianyi@cs.aau.dk) Aalborg University, Denmark
  Wen Qu (quwen@dlut.edu.cn) Liaoning Normal University, China
  Chuanyu Zong (zongcy@sau.edu.cn) Shenyang Aerospace University, China
  Jiaying Wang (jiaying@sut.edu.cn) Shenyang University of Technology, China
  Hongchao Qing (qhc.neu@gmail.com) Beijing Institute of Technology, China
  Ning Wang (wangning@gzhu.edu.cn) Guangzhou University, China
  Shufeng Gong (gongsf@mail.neu.edu.cn) Northeastern University, China
  Mengxiang Wang (wangmx@cnis.ac.cn) China National Institute of Standardization, China