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Machine learning and neural networks tools to address noisy data issues

Contributo in Atti di convegno
Data di Pubblicazione:
2021
Abstract:
In this paper, we present tools for addressing noisy keyword issues in digital libraries. Two tasks, language detection and misspelling detection and correction, are addressed using both machine learning and deep learning techniques. To train and validate the models, different datasets were used/created/scraped. Encouraging preliminary results are presented and discussed.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Content based retrieval; Digital library; Noisy data; Tags; Unsupervised tools
Elenco autori:
Gagliardi, Isabella; Artese, MARIA TERESA
Autori di Ateneo:
ARTESE MARIA TERESA
GAGLIARDI ISABELLA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/417755
Titolo del libro:
Digital Presentation and Preservation of Cultural and Scientific Heritage
Pubblicato in:
DIGITAL PRESENTATION AND PRESERVATION OF CULTURAL AND SCIENTIFIC HERITAGE
Journal
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URL

https://dipp.math.bas.bg/dipp/article/view/dipp.2021.11.8
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