The 2nd International Workshop on Machine Learning and Knowledge Graphs - MLKgraphs2020
Authors will be allowed to present their work virtually if needed to ensure both the safety of participants and wide dissemination of their work.
We will announce further instructions regarding this in the due time.
- Paper submission:
March 16, 2020 March 26, 2020 April 6, 2020April 14, 2020 23:95 GMT (FINAL)
- Notification of acceptance:
May 20, 2020June 1, 2020
- Camera-ready copies due: June 20, 2020
All accepted papers will be published by Springer in "Communications in Computer and Information Science".
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 2nd 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.
TOPICS OF INTEREST
- 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: http://www.dexa.org/formatting_guidelines
Online Papers Submission: https://easychair.org/conferences/?conf=mlkgraphs2020
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.
- Anna Fensel, University of Innsbruck, Austria (firstname.lastname@example.org)
- Bernhard Moser, Software Competence Center Hagenberg, Austria (email@example.com)
- Jorge Martinez-Gil, Software Competence Center Hagenberg, Austria (firstname.lastname@example.org)
- 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
- Vit Novacek, National University of Ireland Galway, Ireland
- 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
- Marina Tropmann-Frick, Hamburg University of Applied Sciences, Germany
- Adrian Ulges, RheinMain University of Applied Sciences, Germany