JARGES: Detecting and Decoding Jargon for Enterprise Search

Colin Daly, Colin Daly, Lucy Hederman, Lucy Hederman

2025

Abstract

Newcomers to an organisation often struggle with unfamiliar internal vocabulary, which can affect their ability to retrieve relevant information. Enterprise Search (ES) systems frequently underperform when queries contain jargon or terminology that is specific to the organisation. This paper introduces `JARGES', a novel feature for detecting and decoding jargon for ES. It is designed to enhance a ranking model combining Learning to Rank (LTR) and transformer-based synonym expansion. The ranking model is evaluated using the ENTRP-SRCH dataset. Our experiments showed, however, that the JARGES feature yielded no significant improvement over the baseline (nDCG@10 = 0.964, $\Delta = 0.001$, p$ > 0.05$). These failures are likely due to the dataset’s lack of jargon-rich pairs. This highlights the need for larger ES datasets derived from click-through data or other implicit feedback to detect subtle ranking signals.

Paper Citation

in Harvard Style

Daly C. and Hederman L. (2025). JARGES: Detecting and Decoding Jargon for Enterprise Search. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 357-363. DOI: 10.5220/0013729500004000

in Bibtex Style

@conference{kdir25,
author={Colin Daly and Lucy Hederman},
title={JARGES: Detecting and Decoding Jargon for Enterprise Search},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={357-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013729500004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - JARGES: Detecting and Decoding Jargon for Enterprise Search
SN -
AU - Daly C.
AU - Hederman L.
PY - 2025
SP - 357
EP - 363
DO - 10.5220/0013729500004000
PB - SciTePress