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MLKgraphs 2021 : The 3rd International Workshop on Machine Learning and Knowledge Graphs


When Sep 27, 2021 - Sep 27, 2021
Where Virtual
Submission Deadline May 2, 2021
Notification Due Jun 1, 2021
Final Version Due Jun 30, 2021
Categories    machine learning   knowledge graphs   data science   ontologies

Call For Papers

The 3rd International Workshop on Machine Learning and Knowledge Graphs (MLKgraphs2021)
September 27 - 30, 2021 - Linz, Austria
Papers submission:

Paper submission: May 2, 2021 (SHARP, Anywhere in the World)
Notification of acceptance: June 1, 2021
Camera-ready copies due: June 30, 2021

All accepted papers will be published by Springer in "Communications in Computer and Information Science".

*** SCOPE ***
Knowledge Graphs are becoming a key technology for large-scale information processing systems containing massive collections of interrelated facts. Specifically, Knowledge Graphs provide the means for development of the newest data methods for data management, data fusion, data merging, and graph optimization and modeling, serving as a source of high quality data and a base for web-scale information integration.
The 3rd International Workshop on Machine Learning and Knowledge Graphs aims to be a meeting point for researchers and practitioners working on the latest advances in the intersection of machine learning technologies and knowledge graphs. Therefore, we welcome submissions of novel research that brings together the two topics of Machine Learning (ML) and Knowledge Graphs (KGs) either applying ML models for semantic data management structures (like KGs or ontologies), or by presenting newly assembled Knowledge Graphs that support the task of Machine Learning for certain application domains. Examples areas are Business Analytics, Customer Relationship Management, Fault Detection, Industry 4.0, or Social Networking.

- Machine Learning (plus its applications such as for Chatbots, Robotics, Social Networks, Fault Detection, Predictive Maintenance, Life Sciences, Neurosciences …) applied on semantic data management structures
- Data Science (including Visual Analytics, Large-Scale Data Processing, and Network Analytics)
- Knowledge Graphs and Ontologies
- State-of-the-art Data Management solutions for Machine Learning applications
- Artificial Intelligence
- Deep Learning
- Cognitive Computing
- Question Answering Systems
- Image Analysis
- Text Analytics
- Industry 4.0
- Internet of Things
- Smart Cities

Authors are invited to submit electronically original contributions in English. Submitted papers should not exceed 10 pages (for a full paper) and 5 pages (for a short paper).
Formatting guidelines:
Online Papers Submission:

Authors of selected papers of the workshop will be invited to submit extended versions of their papers which can be published in a journal special issue after revision.

*** Program Committee Co-chairs ***
- Anna Fensel, University of Innsbruck, Austria (
- Jorge Martinez-Gil, Software Competence Center Hagenberg, Austria (
- Bernhard Moser, Software Competence Center Hagenberg, Austria (

*** Program Committee members ***
- Anastasia Dimou, Ghent University, Belgium
- Lisa Ehrlinger, Johannes Kepler University & Software Competence Center Hagenberg, Austria
- Agata Filipowska, Poznan University of Economics, Poland
- Isaac Lera, University of the Balearic Islands, Spain
- Femke Ongenae, Ghent University, Belgium
- Mario Pichler, Software Competence Center Hagenberg, Austria
- Artem Revenko, Semantic Web Company GmbH, Austria
- Marta Sabou, Vienna University of Technology, Austria
- Harald Sack, Leibniz Institute for Information Infrastructure & KIT Karlsruhe, Germany
- Iztok Savnik, University of Primorska, Slovenia
- Sanju Mishra Tiwari , Universidad Autonoma de Tamaulipas, Mexico
- Marina Tropmann-Frick, Hamburg University of Applied Sciences, Germany

For further inquiries please contact PC chairs/co-Chairs (

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