Curating User Galleries in Europeana using Topic Modeling Technology
Pages 243 - 244
Abstract
Europeana is the European Commission’s platform for cultural heritage aggregating digitized materials from all over the Europe. The Transcribathon tool uses documents from Europeana and enables users to contribute with transcriptions and semantic enrichments. User engagement is stimulated by curating materials of interest for the targeted audience of specific Transcribathon runs. An approach for curating historical materials from Europeana with the use of topic detection technology is showcased in this paper.
References
[1]
Medina Andresel, Sergiu Gordea, Srdjan Stevanetic, and Mina Schütz. 2022. An Approach for Curating Collections of Historical Documents with the Use of Topic Detection Technologies. Int. J. Digit. Curation 17, 1 (2022), 12.
[2]
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, null (mar 2003), 993–1022.
[3]
Roman Egger and Joanne Yu. 2022. A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts. Frontiers in Sociology 7 (2022). https://doi.org/10.3389/fsoc.2022.886498
[4]
Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794 (2022).
Index Terms
- Curating User Galleries in Europeana using Topic Modeling Technology
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Published In
July 2023
797 pages
ISBN:9798400700699
DOI:10.1145/3594806
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
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Published: 10 August 2023
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