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Special Issue "Big Data Analysis Based Network" 

Special Issue Information

A special issue of *Electronics*
< > (ISSN
2079-9292). This special issue belongs to the section "Networks
< >".

Deadline for manuscript submissions: 30 September 2022.

Dear Colleagues,

Entities and their interactive relations are complex and diverse in various
fields, and they are not only huge in number but also rich in variance,
which form a variety of networks, such as electrical power networks,
transportation networks, communication networks, social networks, and
biological networks. Thus, the research on networks is more challenging.
With the rise of big data analysis technology, advances in the perception
and analysis of various networks have been more prosperous. For example,
big data analysis can improve the transmission, distribution, and control
of power in the electrical power networks with the increasing requirement
for greater reliability, efficiency, security, and sustainability of power,
which realize smart management and maintenance.

The main aim of this Special Issue is to seek high-quality submissions that
highlight big data analysis and applications in networks, address recent
breakthroughs in network behaviors, network embedding learning, large-scale
networks, heterogeneous networks, network visualization and storage,
network anomaly analysis, etc. The topics of interest include, but are not
limited to, the following:

   - Big data analysis in complex networks;
   - Network behaviors mining with big data analysis;
   - Network embedding learning technology with big data analysis;
   - Large-scale or heterogeneous network applications;
   - Dynamic spatio-temporal network analysis with big data;
   - Network visualization system with big data analysis;
   - Network structure storage with big data;
   - Network anomaly analysis and detection with big data;
   - Big data applications in electrical power networks, transportation
   networks, communication networks, social networks, and biological networks,

Prof. Dr. Xiangjie Kong
Prof. Dr. Mario Collotta
*Guest Editors*
Xiangjie Kong (孔祥杰), PhD, Professor
CCF Distinguished Member, IEEE Senior Member, ACM Member
Founding-Director, The CSSC Lab ( 
< >)
College of Computer Science and Technology, Zhejiang University of
Technology, Hangzhou 310023, China
Email: [log in to unmask]; [log in to unmask]

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