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ICGT 2026: International Conference on Graph Transformation

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截稿日期:
2026-02-16
通知日期:
2026-04-06
会议日期:
2026-06-29
会议地点:
Rennes, France
届数:
19
ICORE: B   浏览: 15670   关注: 0   参加: 0

会伴指数 (CP-I)

62.9 / 100
全站第 507 名 / 共 5,693 个会议 · 前 9%
学术认可 (35%)
72
投稿选择性 (20%)
54
会议传承 (20%)
81
社区关注 (10%)
10
资料公开度 (15%)
65

用到的输入: 收录等级：ICORE B · 录用率：50.3%（有记录的 5 届的均值） · 有据可查的届次：19 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 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 100% —— 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 2026-10-02

征稿

ICGT 2026 ( International Conference on Graph Transformation) is a ICORE B conference held in Rennes, France on 2026-06-29. The paper submission deadline is 2026-02-16. Acceptance notifications are sent on 2026-04-06.

ICGT welcomes submissions in all topics on graph transformation including, but not limited to: Theoretical Results on, for example: Mathematical models for and approaches to graph transformation Analysis and verification of graph transformation systems Graph grammars and graph languages Application of Graph Transformations, for example: Formal Methods and Graph Transformation Automata on graphs and parsing of graph languages Logical aspects of graph transformation Computational models based on graphs Structuring and modularisation of graph transformation Hierarchical graphs and decomposition of graphs Parallel, concurrent, and distributed graph transformation Term graph and string diagram rewriting Bigraphs and bigraphical reactive systems Petri nets and other models of concurrency Model checking, program analysis and verification, simulation and animation Tools and Development environments Graph transformation languages and tool support Quantum computing, e.g. quantum circuits, graph minor embedding techniques Syntax, semantics and implementation of programming languages, including domain-specific and visual languages Business process models and notations Scene graphs, test environments,test configuration generation Graph databases and graph queries, knowledge bases Model-driven development and model transformation Machine learning and AI, GNNs Graph-based machine learning, including graph neural networks and models of rule inference Graph transformation and artificial intelligence (e.g., AI for graph transformations, applying graph transformations in AI engineering and search-based software engineering) Applications Efficient algorithms (e.g. pattern matching, graph traversal, network analysis) Applications and case studies in software engineering (e.g. software architectures, refactoring, access control, and service-orientation) Applications to computing paradigms (e.g. bio-inspired, quantum, ubiquitous, and visual)
由 Dou Sun 最后更新于

录用率

平均录用率: 51.9% 7 年间 (2015–2021).

年份提交数录用数录用率(%)
2021261453.8%
2020401640%
2019221254.5%
201816956.3%
2017231460.9%
2016331442.4%
2015271555.6%

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CKnowledge-Based Systems7.2Elsevier0950-7051
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