Vol-2997
urn:nbn:de:0074-2997-0

Copyright © 2021 for the individual papers by the papers' authors. Copyright © 2021 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

MLSMKG 2021
Machine Learning with Symbolic Methods and Knowledge Graphs 2021

Machine Learning with Symbolic Methods and Knowledge Graphs
co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021)

Virtual, September 17, 2021.

Edited by

Mehwish Alam *
Mehdi Ali
Paul Groth
Pascal Hitzler *
Jens Lehmann
Heiko Paulheim*
Achim Rettinger *
Harald Sack*
Afshin Sadeghi
Volker Tresp****

* University of Mannheim, Germany,
** University of Bonn, Germany,
*** University of Trier, Germany,
**** University of Munich, Germany,
***** Karlsruhe Institute of Technology(KIT),
****** University of Amsterdam,the Netherlands,
******* Kansas State University, Manhattan, U.S.A.

Table of Contents

Preface
Summary: There were 7 papers submitted for peer-review to this workshop. Out of these, 4 papers were accepted for this volume.

Opening

Session 1:

Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification (1-col) Mirantha Jayathilaka, Tingting Mu , Uli Sattler.

Session 2:

Contextual Graph Representation Learning in Text Disambiguation
Mozhgan Saeidi
Contextual Language Models for Knowledge Graph Completion
Russa Biswas, Radina Sofronova, Mehwish Alam , Harald Sack

Session 3:

On Refining BERT Contextualized Embeddings using Semantic Lexicons
Georgios Zervakis, Emmanuel Vincent, Miguel Couceiro, Marc Schoenauer.

2021-10-04: submitted by Afshin Sadeghi, metadata incl. bibliographic data published under Creative Commons CC0
2021-11-01: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|