Two Huge Title and Keyword Generation Corpora of Research Articles
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424515" target="_blank" >RIV/00216208:11320/20:10424515 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.lrec-1.823" target="_blank" >https://www.aclweb.org/anthology/2020.lrec-1.823</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Two Huge Title and Keyword Generation Corpora of Research Articles
Original language description
Recent developments in sequence-to-sequence learning with neural networks have considerably improved the quality of automatically generated text summaries and document keywords, stipulating the need for even bigger training corpora. Metadata of research articles are usually easy to find online and can be used to perform research on various tasks. In this paper, we introduce two huge datasets for text summarization (OAGSX) and keyword generation (OAGKX) research, containing 34 million and 23 million records, respectively. The data were retrieved from the Open Academic Graph which is a network of research profiles and publications. We carefully processed each record and also tried several extractive and abstractive methods of both tasks to create performance baselines for other researchers. We further illustrate the performance of those methods previewing their outputs. In the near future, we would like to apply topic modeling on the two sets to derive subsets of research articles from more specific dis
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GX19-26934X" target="_blank" >GX19-26934X: Neural Representations in Multi-modal and Multi-lingual Modeling</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020)
ISBN
979-10-95546-34-4
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
6663-6671
Publisher name
European Language Resources Association
Place of publication
Marseille, France
Event location
Marseille, France
Event date
May 11, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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