loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Alexander Paulus ; Andreas Burgdorf ; Alina Stephan ; André Pomp and Tobias Meisen

Affiliation: Chair of Technologies and Management of Digital Transformation, University of Wuppertal, Wuppertal, Germany

Keyword(s): Enterprise Data Management, Knowledge Graphs, Semantic Modeling, Recommender Systems.

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 embed dings 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. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.116.85.96

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 699-708. DOI: 10.5220/0011034900003179

@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 1: ICEIS},
year={2022},
pages={699-708},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011034900003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Using Node Embeddings to Generate Recommendations for Semantic Model Creation
SN - 978-989-758-569-2
IS - 2184-4992
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
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic