Special Section on Progress of Analysis Techniques for Domain-Specific Big Data

Introduction:

Since the concept of big data was first introduced in 2008 in Nature, it has been widely applied in fields such as business, healthcare, education, transportation, national defense and security. As artificial intelligence technologies mature, big data analysis techniques have evolved. Data quality, algorithms, and computing power, however, continue to pose challenges.

The Journal of Electronic Science and Technology (JEST) plans to publish a Special Section on Progress of Analysis Techniques for Domain-Specific Big Data (ATDSBD). We invite all researchers to contribute original articles and review articles that present state-of-the-art research results and industrial applications. We are particularly interested in the studies that describe new techniques for improving the current existing difficulties in the domain-specific big data.

Topics covered:

• Machine learning algorithms for domain-specific big data analysis
• Computer vision algorithms for domain-specific big data analysis
• Natural language processing techniques for domain-specific big data analysis
• Security issues in domain-specific big data analysis
• Challenges faced in domain-specific big data analysis

Important Deadlines:

• Paper Submission: July 31, 2023 (for the first issue of this special section)
• Initial Review Comments Notification: August 31, 2023 (for the first issue of this special section)
• Final Paper Submission: October 8, 2023 (for the first issue of this special section)
• Notification of Acceptance: October 10, 2023 (for the first issue of this special section)

This is a long-term call for papers. After submission, the review processing for the Initial Review Comments Notification is about one month. After that, the revision time for authors is usually one month or less. Accepted papers are published in the ABP style on ScienceDirect. That is, accepted papers will be published online immediately on ScienceDirect with DOI, vol. no. , issue no., and article no., as well as date of acceptance.

Guest Editors:

• Prof. Ling Tian. University of Electronic Science and Technology of China, China. lingtian@uestc.edu.cn                                                     
• Prof. Jianhua Tao.Tsinghua University, China. jhtao@tsinghua.edu.cn
• Dr. Bin Zhou. National University of Defense Technology, China. binzhou@nudt.edu.cn