KGR4XAI 2021:
The 1st International Workshop on Knowledge Graph Reasoning
for Explainable Artificial Intelligence
https://kgr4xai.ikgrc.org/

co-located with
10th International Joint Conference on Knowledge Graphs(IJCKG 2021)
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*** Scope ***

Machine learning has promoted the application of artificial
intelligence(AI) techniques to a wide variety of social problems.
Accordingly, being able to explain the reason for an AI decision
is becoming important to ensure the secure and safe use of AI techniques.

On this background, the Knowledge Graph Reasoning Challenge (KGRC)
has been organized from 2018(*). It aims to promote techniques for
explainable AI using knowledge graphs. The challenge provides a common
task to estimate criminals with a reasonable explanation based on an
open knowledge graph of a well-known Sherlock Holmes mystery story.
Variety of systems and ideas were submitted such as the approach of
constraint satisfaction problem solving, the approach of logical rules
and machine learning techniques including knowledge graph embeddings.
And we had a lot of fruitful discussions.

In this workshop we would like to discuss a wider variety of knowledge
graph reasoning technologies for explainable AI in various domains.
Although one typical topic is to solve mystery stories in the KGRC,
knowledge graphs and related technologies in other domains are also
welcome.

(*)Kawamura T. et al. (2020) Report on the First Knowledge Graph
Reasoning Challenge 2018, JIST 2019. Lecture Notes in Computer
Science, vol 12032. Springer, Cham.


*** Topic of interests ***

Potential topics of interests include, but are not limited to:
- Reasoning on Knowledge Graph
- Reasoning for Knowledge Graph construction and refinement, such as
modeling, authoring, alignment, and completion
- Machine Learning on Knowledge Graph
- Machine Learning for Knowledge Graph construction and refinement
- Explainable AI techniques using Knowledge Graph
- Explainable AI techniques for Knowledge Graph construction and refinement
- Knowledge Graph construction and refinement using reasoning,
Machine Learning and Explainable AI techniques
- Knowledge Graph construction and refinement for reasoning,
Machine Learning and Explainable AI techniques
- Knowledge Graph application and platform using reasoning,
Machine Learning and Explainable AI techniques
- Domain-dependent Knowledge Graph using reasoning, Machine Learning
and Explainable AI techniques
- Semantic system and tool for reasoning, Machine Learning and
Explainable AI techniques
- Ontology design and modelling for reasoning, Machine Learning and
Explainable AI techniques
- The other topics combined aboves


*** Submissions ***

Submissions must be in PDF format, using the latest ACM Proceedings Format
with the default 9pt font (see sample-sigconf.tex or Interim layout.docx
from ACM Primary Article Template).

Paper submissions must be 4-8 pages.

At least one author of each accepted paper must register for the IJCKG
conference and present the paper in the workshop.

Papers can be submitted electronically via EasyChair.
https://easychair.org/conferences/?conf=kgr4xai2021

Accepted papers will be published on the workshop website.
After the conference, the papers will be proposed for publishing at CEUR
Workshop Proceedings. Papers for which authors do not register and
present may be excluded from the proceedings.


*** Important Dates ***

- Paper submission: 23:59 (Hawaii Time), November 17, 2021
- Acceptance Notifications: November 23, 2021
- Camera Ready Submissions: 23:59 (Hawaii Time), November 30, 2021
- Conference Date: December 6, 2021


*** Workshop Organizing Committee ***

- Kouji Kozaki, Osaka Electro-Communication University, Japan
- Takahiro Kawamura, National Agriculture and Food Research
Organization, Japan
- Boris Villazón-Terrazas, Tinámica & International University
of La Rioja (UNIR), Spain
- Marut Buranarach, National Electronics and Computer Technology
Center, Thailand

*** Contact ***
kgr4xai@knowledge-graph.jp