The World Wide Web Journal
Special Issue on "Large-Scale Graph Data Analytics"
Guest Editors: Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang

Manuscript submission deadline now extends to 20 March 2021


Various application domains such as social networks, communication networks, collaboration networks, biological networks, transportation networks, knowledge networks naturally generate large scale graph data to capture the connectedness among entities. Driven by these applications, there is an increasing demand for the development of novel graph analytics models and scalable graph analytics techniques and systems.  The special issue encourages submissions of high-quality research papers in the topic of large-scale graph data analytics from various disciplines including databases, data mining, machine learning, graph theory and algorithms. We also encourage submissions with novel applications of graph techniques to various domains including cybersecurity, healthcare, social networks, business data analytics, etc.

Topics of interest include but are not limited to:
- Graph data model, storage, indexing and query processing techniques
- Graph mining techniques
- Techniques for parallel and distributed graph data processing
- Graph visualization techniques and system interfaces
- Dynamic and streaming graph data analytics
- Spatial-temporal graph analytics
- AI techniques for graphs
- Graph analytics in various application domains such as social networks, semantic web, biological data, business processes, transport data, etc.
- Vision papers to survey the area of graph data analytics as well as describe the future research directions

Submission: 

- Submission is made via the website of The World Wide Web Journal, and select track "Large-scale Graph Data Analytics"
- Submission guidelines: https://www.springer.com/journal/11280/submission-guidelines