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Quantifying the Gradient of Doubt: Framework for Epistemic Uncertainty in Linguistic Hedges

by Bharti, Pawan Tamta
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 13 - Number 2
Year of Publication: 2026
Authors: Bharti, Pawan Tamta
10.5120/ijais2026452045

Bharti, Pawan Tamta . Quantifying the Gradient of Doubt: Framework for Epistemic Uncertainty in Linguistic Hedges. International Journal of Applied Information Systems. 13, 2 ( Mar 2026), 18-33. DOI=10.5120/ijais2026452045

@article{ 10.5120/ijais2026452045,
author = { Bharti, Pawan Tamta },
title = { Quantifying the Gradient of Doubt: Framework for Epistemic Uncertainty in Linguistic Hedges },
journal = { International Journal of Applied Information Systems },
issue_date = { Mar 2026 },
volume = { 13 },
number = { 2 },
month = { Mar },
year = { 2026 },
issn = { 2249-0868 },
pages = { 18-33 },
numpages = {9},
url = { https://www.ijais.org/archives/volume13/number2/quantifying-the-gradient-of-doubt-framework-for-epistemic-uncertainty-in-linguistic-hedges/ },
doi = { 10.5120/ijais2026452045 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-03-11T11:21:17.419946+05:30
%A Bharti
%A Pawan Tamta
%T Quantifying the Gradient of Doubt: Framework for Epistemic Uncertainty in Linguistic Hedges
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 13
%N 2
%P 18-33
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nuanced communication heavily relies on hedges, which are linguistic strategies that convey ambiguity or uncertainty. In many computational tasks, such as sentiment analysis and natural language processing, it is crucial to assess the degree of uncertainty introduced by a hedge accurately. This paper outlines a technique for extracting hedges. It provides a detailed examination of one of their features, specifically the level of fuzziness associated with them, thereby facilitating more efficient information retrieval. Additionally, it aims to lay the groundwork for a "Fuzziness Score" for hedges by investigating key factors, potential methodologies, and associated challenges.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hedges Information retrieval Hedge-Qualifiers Degree of association Nuanced communication

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