Why Do We Need Domain-Experts for End-to-End Text Classification? An Overview

Jakob Andersen

2023

Abstract

The aim of this study is to provide an overview of human-in-the-loop text classification. Automated text classification faces several challenges that negatively affect its applicability in real-world domains. General obstacles are a lack of labelled examples, limited held-out accuracy, missing user trust, run-time constraints, low data quality and natural fuzziness. Human-in-the-loop is an emerging paradigm to continuously support machine processing, i.e. text classification, with prior human knowledge, aiming to overcome the limitations of purely artificial processing. In this survey, we review current challenges of pure automated text classifiers and outline how a human-in-the-loop can overcome these obstacles. We focus on end-to-end text classification and feedback of domain-experts, which do not process technical knowledge about the algorithms used. Further, we discuss common techniques to guide human attention and efforts within the text classification process.

Paper Citation

in Harvard Style

Andersen J. (2023). Why Do We Need Domain-Experts for End-to-End Text Classification? An Overview. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 17-24. DOI: 10.5220/0011605900003393

in Bibtex Style

@conference{icaart23,
author={Jakob Andersen},
title={Why Do We Need Domain-Experts for End-to-End Text Classification? An Overview},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={17-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011605900003393},
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 - Why Do We Need Domain-Experts for End-to-End Text Classification? An Overview
SN - 978-989-758-623-1
AU - Andersen J.
PY - 2023
SP - 17
EP - 24
DO - 10.5220/0011605900003393