Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Pawel Bielski ; Lena Witterauf ; Sönke Jendral ; Ralf Mikut and Jakob Bach

Affiliation: Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

Keyword(s): Ontology Quality Evaluation, Knowledge-Guided Machine Learning, Application Ontology.

Abstract: In this work, we study the critical issue of knowledge mismatch in ontology-guided machine learning (OGML), specifically between domain ontologies and application ontologies. Such mismatches may arise when OGML uses ontological knowledge that was originally created for different purposes. Even if ontological knowledge improves the overall OGML performance, mismatches can lead to reduced performance on specific data subsets compared to machine-learning models without ontological knowledge. We propose a framework to quantify this mismatch and identify the specific parts of the ontology that contribute to it. To demonstrate the framework’s effectiveness, we apply it to two common OGML application areas: image classification and patient health prediction. Our findings reveal that domain-application mismatches are widespread across various OGML approaches, machine-learning model architectures, datasets, and prediction tasks, and can impact up to 40% of unique domain concepts in the datase ts. We also explore the potential root causes of these mismatches and discuss strategies to address them. (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 3.19.213.242

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:
Bielski, P., Witterauf, L., Jendral, S., Mikut, R. and Bach, J. (2024). Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD; ISBN 978-989-758-716-0; ISSN 2184-3228, SciTePress, pages 216-226. DOI: 10.5220/0013065900003838

@conference{keod24,
author={Pawel Bielski and Lena Witterauf and Sönke Jendral and Ralf Mikut and Jakob Bach},
title={Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD},
year={2024},
pages={216-226},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013065900003838},
isbn={978-989-758-716-0},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD
TI - Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning
SN - 978-989-758-716-0
IS - 2184-3228
AU - Bielski, P.
AU - Witterauf, L.
AU - Jendral, S.
AU - Mikut, R.
AU - Bach, J.
PY - 2024
SP - 216
EP - 226
DO - 10.5220/0013065900003838
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