Aim of the Workshop and CFP

Graph model has been widely used in a variety of domains to model the connectedness among entities in real-world organizations and complex systems, such as social networks, communication networks, collaboration networks, e-commerce networks, biological networks, transportation networks, world wide web, and knowledge base. With the rapid development of information technologies in the last decades, the accumulated graph data are becoming larger and larger. The availability of rich graph data not only brings great opportunities for realizing big values of data to serve key applications but also brings great challenges in computation. To enable individuals, business, and organisations to exploit the value of big graph data, there is an increasing demand for novel graph analytics models as well as scalable graph analytics techniques and systems.

The workshop is co-located with the IEEE International Conference on Data Mining (ICDM 2018).

Topics of Interest

• Graph analytics techniques
• Graph mining techniques
• Evaluation measures for graphs
• Machine learning techniques for graphs
• Single-machine graph management Techniques
• External-memory graph management Techniques
• Distributed Graph Management Techniques
• Graph analysis and management of multimedia databases
• Graph analysis and management of semantic web data
• Graph analysis and management of biomedical data
• Graph analysis and management for geometrical applications
• Graph analysis and management for business process management applications
• Advanced applications and tools for graph analysis in different domains