ICKG-2022: IEEE International Conference on Knowledge Graph
November 30-December 1, Orlando, FL, USA
Website: https://ickg2022.zhonghuapu.com/
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Call For papers
l Aims and Scope
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),
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,
maintenance, and inference. ICKG 2022 draws researchers and application
developers from a wide range of Knowledge Graph related areas such as knowledge
engineering, big knowledge, big data analytics, statistics, machine learning,
pattern recognition, data mining, knowledge visualization, high performance
computing, and 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.
Accepted papers will be published in the conference proceedings by the IEEE
Computer Society. Awards will be conferred at the conference on the authors of
the best paper and the best student paper. High quality papers will be invited
for a special issue of Knowledge and Information Systems Journal in an
expanded and revised form.
l Important Dates
o Paper submission (abstract and full paper): July 31, 2022
o Notification of acceptance/rejection: September 11, 2022
o Conference: November 30-December 1, 2022
l Topics of Interest
Foundations, algorithms, models, and theory of Knowledge Graph processing.
o Knowledge engineering with big data.
o Machine learning, data mining, and statistical methods for Knowledge
Graph science and engineering.
o Acquisition, representation and evolution of fragmented knowledge.
o Fragmented knowledge modeling and online learning.
o Knowledge graphs and knowledge maps.
o Knowledge graph security, privacy and trust.
o Knowledge graphs and IoT data streams.
o Geospatial knowledge graphs.
o Ontologies and reasoning.
o Topology and fusion on fragmented knowledge.
o Visualization, personalization, and recommendation of Knowledge Graph
navigation and interaction.
o Knowledge Graph systems and platforms, and their efficiency,
scalability, and privacy.
o Applications and services of Knowledge Graph in all domains including
web, medicine, education, healthcare, and business.
o Big knowledge systems and applications.
o Crowdsourcing, deep learning and edge computing for graph mining.
o Rule and relationship discovery in knowledge graph computing.
l Track Topics
o Track01: Machine Learning and Knowledge Graphs.
o Track02: Reasoning with Knowledge Graphs.
o Track03: Knowledge Graph Analytics and Applications.
o Track04: Knowledge Graphs and NLP.
o Track05: Knowledge graphs for Explainable AI.
o Track06: Multimodal Knowledge Graphs.
o Track07: Social Network and Representation Learning.
o Track08: Knowledge Graphs for Cultural Heritage.
o Track09: Knowledge Graphs for Geospatial Information Systems.
o Track10: Domain Knowledge Graphs.
o Track11: Knowledge Graphs for Education.
o Track12: Big Knowledge Systems.
l Submission Guidelines
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, relevance to
Knowledge Graph, originality, significance, and clarity. You can choose to
identify a Track Topic number in your submission title (e.g.,
your_paper_title-Track01) during submission.
All manuscripts are submitted as full papers and are reviewed based on their
scientific merit. The reviewing process is confidential. There is no separate
abstract submission step. There are no separate industrial, application, short
paper or poster tracks. Manuscripts must be submitted electronically in online
submission system. We do not accept email submissions.
More Information
More information about ICKG 2022 is at
https://ickg2022.zhonghuapu.com/
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