An Automatic Method for Building a Taxonomy of Areas of Expertise

Thu Le, Tuan-Dung Cao, Lam Pham, Trung Pham, Toan Luu

2023

Abstract

Although a lot of Expert finding systems have been proposed, there is a need for a comprehensive study on building a knowledge base of areas of expertise. Building an Ontology creates a consistent lexical framework of a domain for representing information, thus processing the data effectively. This study uses the background knowledge of machine learning methods and textual data mining techniques to build adaptive clustering, local embedding, and term ordering modules. By that means, it is possible to construct an Ontology for a domain via representation language and apply it to the Ontology system of expert information. We proposed a new method called TaxoGenDRK (Taxonomy Generator using Database about Research Area and Keyword) based on the method from Chao Zhang et al. (2018)’s research on TaxoGen and an additional module that uses a database of research areas and keywords retrieved from the internet – the data regarded as an uncertain knowledge base for learning about taxonomy. DBLP dataset was used for testing, and the topic was “computer science”. The evaluation of the topic taxonomy using TaxogenDRK was implemented via qualitative and quantitative methods, producing a relatively good accuracy compared to other existing studies.

Paper Citation

in Harvard Style

Le T., Cao T., Pham L., Pham T. and Luu T. (2023). An Automatic Method for Building a Taxonomy of Areas of Expertise. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 169-176. DOI: 10.5220/0011630500003393

in Bibtex Style

@conference{icaart23,
author={Thu Le and Tuan-Dung Cao and Lam Pham and Trung Pham and Toan Luu},
title={An Automatic Method for Building a Taxonomy of Areas of Expertise},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={169-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011630500003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - An Automatic Method for Building a Taxonomy of Areas of Expertise
SN - 978-989-758-623-1
AU - Le T.
AU - Cao T.
AU - Pham L.
AU - Pham T.
AU - Luu T.
PY - 2023
SP - 169
EP - 176
DO - 10.5220/0011630500003393