BDSME 2023 (International Conference on Big Data Science and Management Engineering) is an academic conference held in Changsha, China on 2023-12-01. The paper submission deadline is 2023-10-07. Acceptance notifications are sent on 2023-11-10.
Since the 21st century, global data has shown an explosive growth trend and the era of big data has arrived. The advent of the Big Data era has brought unprecedented opportunities for higher education institutions to cultivate data science talents, and at the same time brought great challenges. At the meantime, Data science has visualized its impact in engineering management and industrial manufacturing at present. The conference focuses on research areas related to big data science and management engineering aiming to provide a professional academic interchange platform for experts and scholars in related fields to discuss new developments in big data science and management engineering, broaden research ideas, promote the combination of industry, academia, and research, and provide a strong backing for the world economy to achieve a substantial leap forward. Experts from universities, research institutions, business, and other related people are warmly welcomed to submit papers and participate in the conference, where scholars will be able to listen to brilliant presentations by renowned experts and share leading research results and innovative ideas in the industry.
Track 1: Big Data Science
big data mining and analytics
big data applications
database
sensor network and social network for big data
computer science & technology
security applications of big data
big data encryption
natural language processing
information technology
cloud computing techniques for big data
machine learning based on big data
big data visualization
Track 2: Management Engineering
scientific data management
information system management
software management
sensor data management
electronic information technology
big data analysis and its applications
information processing and engineering
information technology and management science
global manufacturing and management
optimizing and optimizing management
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