JIST 2020
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Joint International Conference on Knowledge Graphs
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| Event in series | JIST |
| Dates | 2020-11-20 (iCal) - 2020-11-22 |
| Homepage: | https://language-semantic.org/jist-kg-2020/ |
| Location | |
| Location: | TH/10/Bangkok, TH/10, TH |
| Important dates | |
| Abstracts: | 2020/07/23 |
| Submissions: | 2020/07/30 |
| Table of Contents | |
The Joint International Conference on Knowledge Graphs (JIST-KG) is the 10th JIST-series conference. The mission of JIST-KG 2020 is to bring together researchers in the Knowledge Graph research community and other related areas to present innovative research results and novel applications for Knowledge Graphs.
Call for Papers: Research Track
The JIST-KG 2020 research track solicits submissions of original research work relating to Knowledge Graphs. Topics of interest include, but are not limited to:
- Representation Learning for Knowledge Graphs
- Knowledge Graph Embeddings
- Graph Neural Networks
- Knowledge Graph Construction
- Knowledge Graph Population and Information Extraction
- Knowledge Graph Completion
- Knowledge Graph Quality Assessment and Refinement
- Knowledge Representation and Semantic Reasoning
- Graph Processing Frameworks
- Graph Algorithms and Analytics
- Ontologies and Reasoning
- Semantic Search, Question Answering, and Chatbots
- Graph Databases and Query Languages
- Linked Data and Semantic Data Integration
- Multimodal Knowledge Graphs
- Contextualized Knowledge Graphs
- Cross-modal Semantic Understanding
- Semantic Web Services and Processes
- Trust, Privacy, and Security for Knowledge Graphs
- Blockchain Technologies and Knowledge Graphs
- Open and Enterprise Knowledge Graphs
- Knowledge Graphs for Explainable AI
- Novel Applications of Knowledge Graphs
Important Dates
- Abstract submission: 23:59 (Hawaii Time), July 23, 2020
- Full paper submission: 23:59 (Hawaii Time), July 30, 2020
- Acceptance Notifications: September 10, 2020
- Camera Ready Submissions: 23:59 (Hawaii Time), September 20, 2020
- Conference Date: November 20–22, 2020
Submission
Submissions to JIST-KG 2020 should describe original, significant research on Knowledge Graphs. JIST-KG 2020 will not accept submissions that are under review for or have already been published or accepted for publication in a journal or another conference (*).
(*) Non peer-reviewed documents such as theses, technical reports, publications on preprint server (e.g. arXiv.org) are not considered prior publications. In such cases, JIST-KG 2020 authors are not precluded from submitting papers on the same topic by the same authors.
Submissions to JIST-KG 2020 are expected to present their claimed research contribution, with clear evidence to support their claims.
All submissions will be critically reviewed by at least three members of the Program Committee of the Research Track. To assess submissions, reviewers will judge their relevance to the conference, their originality, technical soundness and depth of their proposed approach, and the readability of the submission.
JIST-KG 2020 submissions are not anonymous.
Submissions must be in PDF format, using the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). Regular paper submissions must be no longer than 16 pages, and short paper submissions must be no longer than 8 pages. Submissions that exceed this limit may be rejected without review. Accepted papers will be published in a Springer LNCS proceedings. At least one author of each accepted paper must register for the conference and present the paper there.
Papers can be submitted electronically via EasyChair (https://easychair.org/conferences/?conf=jistkg2020).
Journal Special Issue
A number of the best papers accepted to JIST-KG 2020 will be recommended to a Special Issue of the Journal of Big Data Research (SCI/ISI/JCR indexed; 2018 IF: 2.952), based on quality, relevance and originality.
Chairs
- Aidan Hogan, DCC, University of Chile, Santiago, Chile
- Thanaruk Theeramunkong, Sirindhorn International Institute of Technology, Pathum Thani, Thailand
- Haofen Wang, Tongji University, Shanghai, China