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Temporal Summarization of Scholarly Paper Collections by Semantic Change Estimation: Case Study of CORD-19 Dataset
- Source :
- Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020, JCDL
- Publication Year :
- 2020
- Publisher :
- ACM, 2020.
-
Abstract
- The new pandemic disease caused by COVID-19 virus is the crucial event over the world in the beginning of 2020. Studies on corona viruses have been however carried since several decades ago, with recent research papers published on weekly basis. We demonstrate a simple approach to explore CORD-19 dataset to provide a high level overview of important semantic changes that occurred over time. Our method aims to support better understanding of large domain-specific collections of scholarly publications that span long time periods and could be regarded as complementary to frequency-based analysis.
- Subjects :
- Estimation
2019-20 coronavirus outbreak
Coronavirus disease 2019 (COVID-19)
Computer science
Event (computing)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
05 social sciences
010501 environmental sciences
01 natural sciences
Data science
Automatic summarization
Semantic change
0502 economics and business
050207 economics
0105 earth and related environmental sciences
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020
- Accession number :
- edsair.doi.dedup.....f53fa529399799fe2a7bd80ce1003c6b
- Full Text :
- https://doi.org/10.1145/3383583.3398563