ICKG2024：IEEE International Conference on Knowledge Graphs

ICKG2024: 15th IEEE International Conference on Knowledge Graphs

Abu Dhabi, UAE, December 11-12

(http://ickg2024.openkg.cn/)

知识图谱作为传统知识工程的代表，是当今最为常用的符号知识表示与存储方式。由于其简单易用，特别在问答、搜索、推荐等场景的成功，使其在工业界及很多领域广泛应用。在大模型时代，知识图谱等符号知识表示方法也被应用于增强大模型的各方面能力。知识图谱与大语言模型的互补增强可以为人工智能提供更加可靠、全面和可控的知识处理技术。IEEE国际知识图谱大会（ICKG）是一个重要的国际性会议，今年和ICDM2024(CCF B)联合举办，旨在展示知识工程、知识图谱、图学习等相关研究方向的原创研究成果，探讨机遇和挑战，以及交流和传播创新的实际开发经验。ICKG 2024旨在吸引来自知识工程、表示学习、大数据分析、统计学、机器学习、模式识别、数据挖掘、知识可视化、高性能计算和万维网等各个领域的研究人员和应用开发人员。欢迎赐稿参会，共同研讨，期待相聚12月阿布扎比。

Overview

The annual IEEE International Conference on Knowledge Graph (ICKG) provides a premier international forum for presentation of original research results in knowledge discovery and graph learning, discussion of opportunities and challenges, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of knowledge discovery from data, with a strong focus on graph learning and knowledge graph, including algorithms, software, platforms. ICKG 2024 intends to draw researchers and application developers from a wide range of areas such as knowledge engineering, representation learning, big data analytics, statistics, machine learning, pattern recognition, data mining, knowledge visualization, high performance computing, and World Wide Web etc. By promoting novel, high quality research findings, and innovative solutions to address challenges in handling all aspects of learning from data with dependency relationship.All accepted papers will be published in the conference proceedings by the IEEE Computer Society. Awards, including Best Paper, Best Paper Runner up, Best Student Paper, Best Student Paper Runner up, will be conferred at the conference, with a check and a certificate for each award. The conference also features a survey track to accept survey papers reviewing recent studies in all aspects of knowledge discovery and graph learning. At least five high quality papers will be invited for a special issue of the Knowledge and Information Systems Journal, in an expanded and revised form.In addition, at least eight quality papers will be invited for a special issue of Data Intelligence Journal in an expanded and revised form with at least 30% difference. We welcome all submissions related to but not limited to the following topics:

• Foundations, algorithms, models, and theory of knowledge discovery and graph learning

• Knowledge engineering with big data.

• Machine learning, data mining, and statistical methods for data science and engineering.

• Acquisition, representation and evolution of fragmented knowledge

• Fragmented knowledge modeling and online learning.

• Knowledge graphs and knowledge maps

• Graph learning security, privacy, fairness, and trust

• Interpretation, rule, and relationship discovery in graph learning

• Geospatial and temporal knowledge discovery and graph learning

• Ontologies and reasoning

• Topology and fusion on fragmented knowledge

• Visualization, personalization, and recommendation of Knowledge Graph navigation and interaction

• Knowledge Graph systems and platforms, and their efficiency, scalability, and privacy

• Applications and services of knowledge discovery and graph learning in all domains including web, medicine, education, healthcare, and business

• Big knowledge systems and applications

• Crowdsourcing, deep learning and edge computing for graph mining

• Large language models and applications 

• Open source platforms and systems supporting knowledge and graph learning

Survey paper reviewing recent study in keep aspects of knowledge discover and graph learning.In addition to the above topics, authors can also select and target the following：

• Special Track 01: KGC and Knowledge Graph Building

• Special Track 02: KR and KG Reasoning

• Special Track 03: KG and Large Language Mode

• Special Track 04: GNN and Graph Learning

• Special Track 05: QA and Graph Database

• Special Track 06: KG and Multi-modal Learning

• Special Track 07: KG and Knowledge Fusion

• Special Track 08: Industry and Applications

Each special track is handled by respective special track chairs, and the papers are also included in the conference proceedings.

Important Dates

• All deadlines are at 11:59PM Pacific Daylight Time

• Paper submission (abstract and full paper): July 31, 2024

• Notification of acceptance/rejection: September 30, 2024

• Camera-ready deadline and copyright forms: October 15, 2024 

• Early Registration Deadline: October 15, 2024

• Conference: December 11-12, 2024

Submission Guidelines

SubmissionURL:

https://wi-lab.com/cyberchair/2024/ickg24/scripts/submit.php?subarea=KG

Paper submissions should be no longer than 8 pages, in the IEEE 2-column format, including the bibliography and any possible appendices. Submissions longer than 8 pages will be rejected without review. All submissions will be reviewed by the Program Committee based on technical quality, originality, significance, and clarity. For survey track paper, please preface the descriptive paper title with “Survey:”, followed by the actual paper title. For example, a paper entitled “A Literature Review of Streaming Knowledge Graph”, should be changed as “Survey: A Literature Review of Streaming Knowledge Graph”. This is for the reviewers and chairs to clearly bid and handle the papers. Once the paper is accepted, the word, such as “Survey:”, can be removed from the camera-ready copy.

For special track paper, please preface the descriptive paper title with “SS##:”, where “##” is the two digits special track ID. For example, a paper entitled “Incremental Knowledge Graph Learning”, intended to target Special Track 01 (Machine learning and knowledge graph) should be changed as “SS01: Incremental Knowledge Graph Learning”.

All manuscripts are submitted as full papers and are reviewed based on their scientific merit. The reviewing process is single blind, meaning that each submission should list all authors and affiliations. There is no separate abstract submission step. There are no separate industrial, application, or poster tracks. Manuscripts must be submitted electronically in the online submission system. No email submission is accepted.To help ensure correct formatting, please use the style files for U.S. Letter as template for your submission. These include LaTeX and Word.Key DatesImportant Dates of the Conference.

General Chairs

Prof. Xingquan(HILL) ZHU, Florida Atlantic University, USA

Prof. Roger Wattenhofer,ETH Zurich, Switzerland

Program Chairs

Prof. Huajun Chen,Zhejiang University, China

Prof. Anna Fensel,Wageningen University，Netherlands

OpenKG

OpenKG（中文开放知识图谱）旨在推动以中文为核心的知识图谱数据的开放、互联及众包，并促进知识图谱算法、工具及平台的开源开放。

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