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ICBDSE 2026: International Conference on Big Data Science and Engineering

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ICBDSE
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截稿日期:
2026-04-12
通知日期:
2026-05-22
会议日期:
2026-06-12
会议地点:
Kunming, China
届数:
3
浏览: 6295   关注: 0   参加: 0

会伴指数 (CP-I)

41.7 / 100
全站第 4,689 名 / 共 5,682 个会议 · 前 83%

数据挖掘与数据库 第 276 / 337

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
37
社区关注 (10%)
15
资料公开度 (15%)
35

用到的输入: 有据可查的届次：3 · 过去 24 个月打开过本页的研究者：6 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-15

征稿

ICBDSE 2026 (International Conference on Big Data Science and Engineering) is an academic conference held in Kunming, China on 2026-06-12. The paper submission deadline is 2026-04-12. Acceptance notifications are sent on 2026-05-22.

About ICBDSE 2026 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 and industrial manufacturing at present. The conference focuses on research areas related to big data science and 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 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. Call for Papers Big Data Mining and Analytics Big Data Applications Database Security Applications of Big Data Big Data Encryption Information Technology Cloud Computing Techniques for Big Data Machine Learning Based on Big Data Big Data Visualization Distributed Storage Systems Data Privacy and Security Machine Learning Algorithms Deep Learning Algorithms Graph Algorithms Reinforcement Learning Algorithms Unsupervised Learning Algorithms Anomaly Detection Algorithms Agricultural Big Data Analysis Stream Processing Systems Big Data Storage and Retrieval Data Mining Systems
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