会议信息

KSEM 2026: International Conference on Knowledge Science, Engineering and Management

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截稿日期:
2026-02-28
通知日期:
2026-03-31
会议日期:
2026-07-17
会议地点:
Beijing, China
届数:
CCF: C   ICORE: C   QUALIS: B3   浏览: 641584   关注: 229   参加: 81
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KSEM
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会伴指数 (CP-I)

64.8 / 100
全站第 443 名 / 共 5,693 个会议 · 前 8%

人工智能与机器学习 第 32 / 742

学术认可 (35%)
66
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
81
社区关注 (10%)
74
资料公开度 (15%)
55

用到的输入: 收录等级：CCF C, ICORE C, QUALIS B3 · 有据可查的届次：19 · 在会伴关注它的研究者：229 人 · 过去 24 个月打开过本页的研究者：16 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 1.1 · 算于 2026-10-06

征稿

KSEM 2026 (International Conference on Knowledge Science, Engineering and Management) is a CCF C / ICORE C / QUALIS B3 conference held in Beijing, China on 2026-07-17. The paper submission deadline is 2026-02-28. Acceptance notifications are sent on 2026-03-31.

For KSEM 2026, we are particularly focused on the theme of applied knowledge science and engineering in networking and cybersecurity, which includes the use of large language models (LLM). Submissions are not limited to these topics, and we welcome contributions across a broad range of areas, as detailed below: Knowledge Science • Knowledge representation and reasoning • Formal analysis of knowledge; reasoning about knowledge • Knowledge complexity and knowledge metrics • Uncertainty in knowledge (randomness, fuzziness, roughness, vagueness) • Knowledge fusion for decision making • Formal ontologies • Reasoning about knowledge in the presence of inconsistency, incompleteness and context-dependency • Belief propagation, revision and aggregation • Cognitive foundations of knowledge • Integration of machine learning and knowledge representation • Knowledge-driven learning • Knowledge for cognitive robotics • Knowledge for cognitive analytics • Knowledge in complex systems (e.g. manufacture assembling, economical and quantum systems) • Game-theoretical aspects of knowledge; knowledge in multi-agent systems Knowledge Engineering • Knowledge modeling • Knowledge acquisition, such as knowledge modules, temporal knowledge, etc. • Knowledge extraction from texts/videos, big data/Web • Knowledge discovery from very large databases • Knowledge integration • Knowledge-based software engineering • Knowledge-based systems in life sciences • Knowledge-based systems for smart homes • Conceptual modeling in knowledge-based systems • Semantic database systems • Semantic Web: Content and ontological engineering • Knowledge engineering applications • Knowledge-based system and Large Language Models (LLMs) Knowledge Management • Knowledge management best practices and applications • Knowledge verification and validation (e.g. Blockchain) • Knowledge protection and attack detection • Knowledge-Based Systems in Cybersecurity Threat Detection and Intelligent Decision-Making • Smart knowledge and resource optimization • Knowledge dissemination • Knowledge management systems • Knowledge and data integration • Knowledge adaptation Knowledge Graphs • Knowledge graph storage and management • Probabilistic knowledge graphs • Knowledge graph construction • Knowledge graph query • Learning on knowledge graphs • Knowledge graph embedding • Knowledge graph completion • Multi-modal knowledge graphs • Knowledge graph applications • Deep graph neural networks
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CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
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CIEEE Transactions on Industrial Informatics11.7IEEE1551-3203
CIEEE Internet of Things Journal8.9IEEE2327-4662
CEngineering Applications of Artificial Intelligence9.0Elsevier0952-1976
CExpert Systems with Applications7.5Elsevier0957-4174
CIEEE Transactions on Big Data5.7IEEE2332-7790

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