会议信息

ICPM 2027: International Conference on Process Mining

请登录查看会议网址
免费注册：查看官网链接、跟踪截稿日期，并接收邮件提醒。
注册 登录
截稿日期:
2026-09-04 已截稿
通知日期:
2026-11-04
会议日期:
2027-02-08
会议地点:
Rende, Italy
届数:
ICORE: B   浏览: 15520   关注: 2   参加: 1
这一页信息有误？告诉我们
嵌入截止倒计时徽章
ICPM
用 API 获取这条数据
搜索与榜单列表完全无需凭证；本页的完整详情需要一把免费 API 密钥。详见开发者接入页。

会伴指数 (CP-I)

58.1 / 100
全站第 688 名 / 共 5,721 个会议 · 前 13%
学术认可 (35%)
72
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
59
社区关注 (10%)
28
资料公开度 (15%)
55

用到的输入: 收录等级：ICORE B · 有据可查的届次：8 · 在会伴关注它的研究者：2 人 · 过去 24 个月打开过本页的研究者：9 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 2026-10-19

征稿

ICPM 2027 (International Conference on Process Mining) is a ICORE B conference held in Rende, Italy on 2027-02-08. The paper submission deadline is 2026-09-04. Acceptance notifications are sent on 2026-11-04.

The International Conference on Process Mining (ICPM) is the premier international venue for researchers and professionals working in the field of process mining. It promotes a vibrant exchange of ideas and expertise through scientific presentations, interactive industry sessions, live challenges, practical tutorials, and expert-led panels. ICPM addresses the full spectrum of process mining research and practice, spanning theoretical progress, algorithmic research, real-world impact and applications, and interdisciplinary links with areas such as machine learning, data science, and operations management. Supported by the IEEE Task Force on Process Mining, ICPM stands at the forefront of innovation in process mining research and practice. Process mining reshapes the way organizations explore, analyze, and optimize their operational processes by deriving insights from transactional data stored in information systems. This evidence- driven approach allows organizations to improve their processes across critical dimensions, including efficiency, quality, compliance, and risk management. By moving beyond traditional assumption-based methods toward data-driven decision-making, process mining opens new avenues for advancing business process management. Topics for Research Papers ICPM 2027 welcomes rigorous contributions spanning both technical and empirical process mining research, aiming to advance the state of the art and expand existing knowledge in the field. Submissions should explicitly articulate their original contributions and novelty. Submissions are encouraged to provide an evaluation appropriate to their contribution. This may involve theoretical demonstrations and examples (for conceptual and theoretical work), quantitative or comparative analysis (for technical work), or evidence of practical relevance such as case studies or newly collected data (for empirical work). Studies utilizing novel, unpublished datasets are particularly welcomed. Research using existing datasets must emphasize the novelty of the analysis or its unprecedented results. To enhance transparency, reproducibility, and replicability, authors are strongly encouraged to provide supplementary resources, such as used datasets, publicly accessible implementations, and experimental packages for empirical studies. For more details, please consult the Open Science Principles section below. Selected accepted papers may be invited for an extended and revised publication in a special issue of the flagship journal Process Science (https://link.springer.com/journal/44311). ICPM 2027 welcomes submissions across a broad spectrum of topics, including but not limited to: Technical Research in Process Mining ● Novel process mining methods and techniques for: ○ Event log building and preprocessing ○ Process discovery ○ Conformance checking ○ Performance analysis ○ Comparative process mining ○ Predictive and prescriptive process monitoring ○ Action-oriented process mining ● Formal foundations of process mining ● Conceptual models related to process mining ● Process mining visualizations Empirical Research in Process Mining ● Case studies and applications ● Experiments involving process mining methods and techniques ● Human-in-the-loop studies ● Survey- and interview-based studies
由 Admin Agent 最后更新于

相关会议

相关期刊

CCF全称影响因子出版商ISSN
Journal of Process Control3.9Elsevier0959-1524
BJournal of Software: Evolution and Process1.8Wiley2047-7481
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203

评论 0

暂无评论。

请登录后发表评论