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Çano, Erion, 2019, OAGSX Title Generation Dataset, LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL), http://hdl.handle.net/11234/1-3079.
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dc.contributor.authorÇano, Erion
dc.date.accessioned2019-10-31T09:04:42Z
dc.date.available2019-10-31T09:04:42Z
dc.date.issued2019-11-01
dc.descriptionOAGSX is a title generation dataset consisting of 34408509 abstracts and titles from scientific articles. The 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. The data is derived from OAG data collection (https://aminer.org/open-academic-graph) which was released under ODC-BY license. This data (OAGSX Title Generation Dataset) is released under CC-BY license (https://creativecommons.org/licenses/by/4.0/). If using it, please consider citing also the following paper: Çano Erion, Bojar Ondřej. Two Huge Title and Keyword Generation Corpora of Research Articles. LREC 2020, Proceedings of the the 12th International Conference on Language Resources and Evaluation, Marseille, France, May 2020.
dc.identifier.urihttp://hdl.handle.net/11234/1-3079
dc.language.isoeng
dc.publisherCharles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/825460
dc.relation.isreferencedbyhttps://www.aclweb.org/anthology/2020.lrec-1.823
dc.relation.replaceshttp://hdl.handle.net/11234/1-3043
dc.rightsCreative Commons - Attribution 4.0 International (CC BY 4.0)
dc.rights.labelPUB
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectTitle Generation Dataset
dc.subjectAbstractive Text Summarization
dc.subjectScientific Papers Corpus
dc.titleOAGSX Title Generation Dataset
dc.typecorpus
local.brandingLINDAT / CLARIAH-CZ
local.contact.personErion Çano cano@ufal.mff.cuni.cz Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
local.files.count2
local.files.size13363564729
local.has.filesyes
local.language.nameEnglish
local.size.info33 files
local.size.info38.8 gb
local.size.info34408509 entries
local.size.info12.4 gb
local.sponsornationalFunds CZ.02.2.69/0.0/0.0/16_027/0008495 Ministerstvo školství, mládeže a tělovýchovy České republiky OP VVV Mezinárodní mobilita výzkumných pracovníků Univerzity Karlovy
local.sponsoreuFunds H2020-ICT-2018-2-825460 European Union ELITR - European Live Translator info:eu-repo/grantAgreement/EC/H2020/825460
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    OAGSX Title Generation Dataset
==============================

OAGSX is a title generation dataset consisting
of 34408509 abstracts and titles from scientific 
articles. The 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. 

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

This data (OAGSX Title Generation Dataset) is released under 
CC-BY license (https://creativecommons.org/licenses/by/4.0/). 


Download
--------

This dataset can be download from LINDAT/CLARIN repository
http://hdl.handle.net/11234/1-3079


Publications
------------

If using it, please cite the following paper:

Çano Erion, Bojar Ondřej. Two Huge Title and Keyword Generation Corpora of Research Articles. 
LREC 2020, Proceedings of the the 12th International Conference on Language Resources and Evaluation, 
Marseille, France, May 2020


Acknowledgements
----------------

This research work was [partially] supported by OP RDE project No. 
CZ.02.2.69/0.0/0.0/16_027/0008495, International Mobility of 
Researchers at Charles University.


Statistics of OAGSX:
--------------------

Total samples:     	34408509 
Title tokens	   	mean: 13.04 std: 5.13 min: 3 max: 25
Abstract tokens 	mean: 182.19 std: 89.20 min: 50 max: 400
Abs-Tit overlap		mean: 0.7713 std: 0.1796
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