Supporting Taxonomy Development and Evolution by Means of Crowdsourcing

Binh Vu, Matthias Hemmje

2019

Abstract

Information overload continues to be a challenge. By dividing the material into many different small subsets, classification based on a taxonomy makes data exploration and retrieval faster and more accurate. Instead of having to know the exact keywords that describe the knowledge resource, users can browse and search for them by selecting the categories that the resource is most likely to belong. Nevertheless, developing taxonomies is not an easy task. It requires the authors to have a certain amount of knowledge in the domain. Furthermore, the workload will increase as any new taxonomy needs to be frequently updated to remain relevant and useful. To combat these problems, this paper proposes another approach to crowdsource taxonomy development and evolution. We describe in this paper the concept of this approach along with different types of evaluations targeting on the one hand to demonstrate the feasibility of the approach and the usability of the initial prototype as well as on the other hand the quality and effectiveness of the chosen method.

Paper Citation

in Harvard Style

Vu B. and Hemmje M. (2019). Supporting Taxonomy Development and Evolution by Means of Crowdsourcing. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD; ISBN 978-989-758-382-7, SciTePress, pages 351-358. DOI: 10.5220/0008348003510358

in Bibtex Style

@conference{keod19,
author={Binh Vu and Matthias Hemmje},
title={Supporting Taxonomy Development and Evolution by Means of Crowdsourcing},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD},
year={2019},
pages={351-358},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008348003510358},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD
TI - Supporting Taxonomy Development and Evolution by Means of Crowdsourcing
SN - 978-989-758-382-7
AU - Vu B.
AU - Hemmje M.
PY - 2019
SP - 351
EP - 358
DO - 10.5220/0008348003510358
PB - SciTePress