Knowledge Graph deals with fragmented knowledge from heterogeneous, autonomous information sources for complex and evolving relationships, in addition to domain expertise. The IEEE International Conference on Knowledge Graph (ICKG), entitled ICBK in some of the previous years, provides a premier international forum for presentation of original research results in Knowledge Graph opportunities and challenges, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of Knowledge Graph, including algorithms, software, platforms, and applications for knowledge graph construction, maintainence and inference. ICKG draws researchers and application developers from a wide range of Knowledge Graph related areas such as knowledge engineering, knowledge graph systems, big data analytics, Big Knowledge, statistics, machine learning, pattern recognition, data mining, knowledge visualization, high performance computing, and the World Wide Web. By promoting novel, high quality research findings, and innovative solutions to challenging Knowledge Graph problems, the conference seeks to continuously advance the state-of-the-art in Knowledge Graph.
ICKG is held annually. The table below shows the locations and conference dates since 2017.
|2023 (12/1-12/2) Shanghai||2022 (11/30-12/1) Orlando, FL, USA|
|2021 (12/7-12/8) Auckland||2020 (8/9-8/10) Nanjing|
|2019 (11/10-11/11) Beijing||2018 (11/17-11/18) Singapore|
|2017 (8/9-8/10) Hefei|
The Steering Committee coordinates the conference series. It decides where and when the next conference will be held, and selects the Program Chair(s).
The ICKG proceedings are published by the IEEE Computer Society Press each year. A selected number of ICKG top-ranked papers will be expanded and revised for possible inclusion in the KAIS journal (Knowledge and Information Systems, by Springer every year. This will be mentioned in all calls for papers of the ICKG conference.