@inproceedings{eklund-etal-2024-ciphe,
title = "{CIPHE}: A Framework for Document Cluster Interpretation and Precision from Human Exploration",
author = "Eklund, Anton and
Forsman, Mona and
Drewes, Frank",
editor = {H{\"a}m{\"a}l{\"a}inen, Mika and
{\"O}hman, Emily and
Miyagawa, So and
Alnajjar, Khalid and
Bizzoni, Yuri},
booktitle = "Proceedings of the 4th International Conference on Natural Language Processing for Digital Humanities",
month = nov,
year = "2024",
address = "Miami, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.nlp4dh-1.52",
pages = "536--548",
abstract = "Document clustering models serve unique application purposes, which turns model quality into a property that depends on the needs of the individual investigator. We propose a framework, Cluster Interpretation and Precision from Human Exploration (CIPHE), for collecting and quantifying human interpretations of cluster samples. CIPHE tasks survey participants to explore actual document texts from cluster samples and records their perceptions. It also includes a novel inclusion task that is used to calculate the cluster precision in an indirect manner. A case study on news clusters shows that CIPHE reveals which clusters have multiple interpretation angles, aiding the investigator in their exploration.",
}
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<abstract>Document clustering models serve unique application purposes, which turns model quality into a property that depends on the needs of the individual investigator. We propose a framework, Cluster Interpretation and Precision from Human Exploration (CIPHE), for collecting and quantifying human interpretations of cluster samples. CIPHE tasks survey participants to explore actual document texts from cluster samples and records their perceptions. It also includes a novel inclusion task that is used to calculate the cluster precision in an indirect manner. A case study on news clusters shows that CIPHE reveals which clusters have multiple interpretation angles, aiding the investigator in their exploration.</abstract>
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%0 Conference Proceedings
%T CIPHE: A Framework for Document Cluster Interpretation and Precision from Human Exploration
%A Eklund, Anton
%A Forsman, Mona
%A Drewes, Frank
%Y Hämäläinen, Mika
%Y Öhman, Emily
%Y Miyagawa, So
%Y Alnajjar, Khalid
%Y Bizzoni, Yuri
%S Proceedings of the 4th International Conference on Natural Language Processing for Digital Humanities
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, USA
%F eklund-etal-2024-ciphe
%X Document clustering models serve unique application purposes, which turns model quality into a property that depends on the needs of the individual investigator. We propose a framework, Cluster Interpretation and Precision from Human Exploration (CIPHE), for collecting and quantifying human interpretations of cluster samples. CIPHE tasks survey participants to explore actual document texts from cluster samples and records their perceptions. It also includes a novel inclusion task that is used to calculate the cluster precision in an indirect manner. A case study on news clusters shows that CIPHE reveals which clusters have multiple interpretation angles, aiding the investigator in their exploration.
%U https://aclanthology.org/2024.nlp4dh-1.52
%P 536-548
Markdown (Informal)
[CIPHE: A Framework for Document Cluster Interpretation and Precision from Human Exploration](https://aclanthology.org/2024.nlp4dh-1.52) (Eklund et al., NLP4DH 2024)
ACL