OAGK Keyword Generation Dataset

PID

OAGK is a keyword extraction/generation dataset consisting of 2.2 million abstracts, titles and keyword strings from cientific articles. Texts were lowercased and tokenized with Stanford CoreNLP tokenizer. No other preprocessing steps were applied in this release version. Dataset records (samples) are stored as JSON lines in each text file.

This data is derived from OAG data collection (https://aminer.org/open-academic-graph) which was released under ODC-BY licence.

This data (OAGK Keyword Generation Dataset) is released under CC-BY licence (https://creativecommons.org/licenses/by/4.0/).

If using it, please cite the following paper: Çano, Erion and Bojar, Ondřej, 2019, Keyphrase Generation: A Text Summarization Struggle, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, June 2019, Minneapolis, USA

Identifier
PID http://hdl.handle.net/11234/1-2943
Related Identifier https://www.aclweb.org/anthology/N19-1070
Related Identifier http://hdl.handle.net/11234/1-3062
Metadata Access http://lindat.mff.cuni.cz/repository/oai/request?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:lindat.mff.cuni.cz:11234/1-2943
Provenance
Creator Çano, Erion
Publisher Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Publication Year 2019
Funding Reference info:eu-repo/grantAgreement/EC/H2020/825460
Rights Creative Commons - Attribution 4.0 International (CC BY 4.0); http://creativecommons.org/licenses/by/4.0/; PUB
OpenAccess true
Contact lindat-help(at)ufal.mff.cuni.cz
Representation
Language English
Resource Type corpus
Format text/plain; charset=utf-8; text/plain; application/zip; downloadable_files_count: 2
Discipline Linguistics