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Intuitive semantic graph tool for enhanced archive exploration

Poster
Data di Pubblicazione:
2023
Abstract:
The paper introduces a new method for visualizing and navigating information in a cultural heritage archive in a simple and intuitive way. The proposed approach employs pre-trained language models to cluster data and create semantic graphs. The creation of multi-layer maps enables deep exploration of archives with large datasets, while the ability to handle multilingual datasets makes it suitable for archives with documents in various languages. These features combine to provide a user-friendly tool that can be adapted to different contexts and provides an overview of archive contents, to allow even non expert users to successfully query the archive.
Tipologia CRIS:
04.03 Poster in Atti di convegno
Keywords:
Bert; pre-trained language models; transformers; clustering; data visualization; archives; non-expert users
Elenco autori:
Gagliardi, Isabella; Artese, MARIA TERESA
Autori di Ateneo:
ARTESE MARIA TERESA
GAGLIARDI ISABELLA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/461939
Titolo del libro:
HT'23: Proceedings of the 34th ACM Conference on Hypertext and Social Media
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URL

https://dl.acm.org/doi/10.1145/3603163.3609069
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