Using Node Embeddings to Generate Recommendations for Semantic Model Creation

Alexander Paulus, Andreas Burgdorf, Alina Stephan, André Pomp, Tobias Meisen

2022

Abstract

With the ongoing digitalization and the resulting growth in digital heterogeneous data, it is becoming increasingly important for enterprises to manage and control this data. An approach that has established itself over the past years for managing heterogeneous data is the creation and use of knowledge graphs. However, creating a knowledge graph requires the generation of a semantic mapping in the form of a semantic model between datasets and a corresponding ontology. Even though the creation of semantic models can be partially automated nowadays, manual adjustments to the created models are often required, as otherwise no reliable results can be achieved in many real-world use cases. In order to support the user in the refinement of those automatically created models, we propose a content-based recommender system that, based on the present semantic model, automatically suggests concepts that reasonably complement or complete the present semantic model. The system utilizes node embeddings to extract semantic concepts from a set of existing semantic models and utilize these in the recommendation. We evaluate accuracy and usability of our approach by performing synthetic modeling steps upon selected datasets. Our results show that our recommendations are able to identify additional concepts to improve auto-generated semantic models.

Paper Citation

in Harvard Style

Paulus A., Burgdorf A., Stephan A., Pomp A. and Meisen T. (2022). Using Node Embeddings to Generate Recommendations for Semantic Model Creation. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 699-708. DOI: 10.5220/0011034900003179

in Bibtex Style

@conference{iceis22,
author={Alexander Paulus and Andreas Burgdorf and Alina Stephan and André Pomp and Tobias Meisen},
title={Using Node Embeddings to Generate Recommendations for Semantic Model Creation},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={699-708},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011034900003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Using Node Embeddings to Generate Recommendations for Semantic Model Creation
SN - 978-989-758-569-2
AU - Paulus A.
AU - Burgdorf A.
AU - Stephan A.
AU - Pomp A.
AU - Meisen T.
PY - 2022
SP - 699
EP - 708
DO - 10.5220/0011034900003179