会议信息

IDEAS 2027: International Database Engineering and Artificial Intelligence Symposium

截稿日期:
2026-11-15 今天截止
通知日期:
2026-12-15
会议日期:
2027-01-25
会议地点:
Fukuoka, Japan
届数:
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ICORE: C   浏览: 26425   关注: 5   参加: 0
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会伴指数 (CP-I)

60.6 / 100
全站第 609 名 / 共 5,777 个会议 · 前 11%

数据挖掘与数据库 第 32 / 340

学术认可 (35%)
58
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
93
社区关注 (10%)
34
资料公开度 (15%)
55

用到的输入: 收录等级：ICORE C · 有据可查的届次：31 · 在会伴关注它的研究者：5 人 · 过去 24 个月打开过本页的研究者：8 人

公开资料里还缺: 历年录用率 (+4.5) · 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 80% —— 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 1.2 · 算于 2026-11-14

征稿

IDEAS 2027 (International Database Engineering and Artificial Intelligence Symposium) is a ICORE C conference held in Fukuoka, Japan on 2027-01-25. The paper submission deadline is 2026-11-15. Acceptance notifications are sent on 2026-12-15.

The IDEAS series provides an international forum for discussion of the problems of engineering data driven systems involving not only database technology but the related areas of artificial intelligence, information retrieval, multimedia, human machine interface, speech, natural language processing and communication. The goal of IDEAS is to foster closer interaction among the industrial, research and user communities and provides an excellent opportunity for them to meet, discuss ideas, examine the current ones and develop new solutions and research directions. Along with the technical sessions, the symposium also features prominent invited speakers. The series are scheduled annually and have been held since 1997 in North America, Europe and Asia. It has attracted participants from governmental and non-governmental agencies, industries, and academia to exchange ideas and share experiences. IDEAS 2027 has expanded its scope to include AI and database engineering works. Topics include, but not limited to: -Artificial intelligence (AI) and its applications -Big data applications -Big data and scalable analytics -Data management -Data mining -Data quality, cleaning and provenance -Data warehousing and OLAP -Databases -Deep learning and neural models -Ethics in AI, AI for social good -Explainable AI -Fair, secure, private, and trusted AI -Human-machine interface -Information retrieval and search -Knowledge management -Knowledge representation -Large language models (LLMs) -Link and graph mining -Multimedia -Natural language processing (NLP) -Social media and social networks -Statistical and scientific data -Stream, spatial and temporal and dimensional data -Speech -Web and cyber security -Web mining and applications
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C57.2AISCAustralasian Information Security Conference2026-11-152027-02-01

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