Evaluation of a System for Named Entity Recognition in a Knowledge Management Ecosystem

Philippe Tamla, Florian Freund, Matthias Hemmje, Paul Mc Kevitt

2022

Abstract

In this research paper, the evaluation of a new system for machine learning-based Named Entity Recognition is presented. After introducing our approach supporting two fundamental tasks for training Named Entity Recognition models using machine learning (data cleanup and data annotation), our features, prototype and evaluation methodologies are described. Also, the results of our performed quantitative and qualitative experiments validating our approach and user interface are shown. Finally, our evaluation results are discussed to derive challenges for future work.

Paper Citation

in Harvard Style

Tamla P., Freund F., Hemmje M. and Mc Kevitt P. (2022). Evaluation of a System for Named Entity Recognition in a Knowledge Management Ecosystem. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD; ISBN 978-989-758-614-9, SciTePress, pages 19-31. DOI: 10.5220/0011374000003335

in Bibtex Style

@conference{keod22,
author={Philippe Tamla and Florian Freund and Matthias Hemmje and Paul Mc Mc Kevitt},
title={Evaluation of a System for Named Entity Recognition in a Knowledge Management Ecosystem},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD},
year={2022},
pages={19-31},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011374000003335},
isbn={978-989-758-614-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD
TI - Evaluation of a System for Named Entity Recognition in a Knowledge Management Ecosystem
SN - 978-989-758-614-9
AU - Tamla P.
AU - Freund F.
AU - Hemmje M.
AU - Mc Kevitt P.
PY - 2022
SP - 19
EP - 31
DO - 10.5220/0011374000003335
PB - SciTePress