Zobrazit minimální záznam

 
dc.contributor.author Çano, Erion
dc.date.accessioned 2019-10-21T13:30:24Z
dc.date.available 2019-10-21T13:30:24Z
dc.date.issued 2019-10-21
dc.identifier.uri http://hdl.handle.net/11234/1-3062
dc.description OAGKX is a keyword extraction/generation dataset consisting of 22674436 abstracts, titles and keyword strings 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 (OAGKX Keyword Generation Dataset) is released under CC-BY license (https://creativecommons.org/licenses/by/4.0/). If using it, please cite the following paper: Çano Erion, Bojar Ondřej. Keyphrase Generation: A Multi-Aspect Survey. FRUCT 2019, Proceedings of the 25th Conference of the Open Innovations Association FRUCT, Helsinki, Finland, Nov. 2019 To reproduce the experiments in the above paper, you can use the first 100000 lines of part_0_0.txt file.
dc.language.iso eng
dc.publisher Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
dc.relation info:eu-repo/grantAgreement/EC/H2020/825460
dc.relation.isreferencedby https://ieeexplore.ieee.org/document/8981519
dc.relation.replaces http://hdl.handle.net/11234/1-2943
dc.rights Creative Commons - Attribution 4.0 International (CC BY 4.0)
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject keyword extraction
dc.subject supervised keyword generation
dc.subject abstractive keyphrasing
dc.title OAGKX Keyword Generation Dataset
dc.type corpus
metashare.ResourceInfo#ContentInfo.mediaType text
dc.rights.label PUB
has.files yes
branding LINDAT / CLARIAH-CZ
contact.person Erion Çano cano@ufal.mff.cuni.cz Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
sponsor Ministerstvo školství, mládeže a tělovýchovy České republiky CZ.02.2.69/0.0/0.0/16_027/0008495 OP VVV Mezinárodní mobilita výzkumných pracovníků Univerzity Karlovy nationalFunds
sponsor European Union H2020-ICT-2018-2-825460 ELITR - European Live Translator euFunds info:eu-repo/grantAgreement/EC/H2020/825460
size.info 22674436 entries
size.info 37 files
size.info 27.4 gb
size.info 8.5 gb
files.size 9139358485
files.count 2


 Soubory tohoto záznamu

Licenční kategorie:
Publicly Available

Licence: Creative Commons - Attribution 4.0 International (CC BY 4.0)
Distributed under Creative Commons Attribution Required
Icon
Název
oagkx.zip
Velikost
8.51 GB
Formát
application/zip
Popis
data
MD5
8a6475ea0d5a38c7aff97a0f5260df20
 Stáhnout soubor  Náhled
 Náhled souboru  
  • oagkx
    • part_11_0.txt11 MB
    • part_3_1.txt1 GB
    • part_0_1.txt900 MB
    • part_13_0.txt69 MB
    • part_10_0.txt873 MB
    • part_2_1.txt1 GB
    • part_12_0.txt11 MB
    • part_5_1.txt877 MB
    • part_1_1.txt867 MB
    • part_14_0.txt1 GB
    • part_7_1.txt120 MB
    • part_4_1.txt1 GB
    • part_9_1.txt867 MB
    • part_6_1.txt1 GB
    • part_8_1.txt541 MB
    • part_0_0.txt752 MB
    • part_3_0.txt1 GB
    • part_5_0.txt1 GB
    • part_2_0.txt1 GB
    • part_7_0.txt1 GB
    • part_4_0.txt1 GB
    • part_1_0.txt1 GB
    • part_9_0.txt709 MB
    • part_6_0.txt789 MB
    • part_8_0.txt561 MB
    • part_11_1.txt9 MB
    • part_13_1.txt108 MB
    • part_10_1.txt58 MB
    • part_3_2.txt437 MB
    • part_0_2.txt770 MB
    • part_5_2.txt880 MB
    • part_2_2.txt345 MB
    • part_12_1.txt9 MB
    • part_4_2.txt568 MB
    • part_1_2.txt759 MB
    • part_14_1.txt1 GB
    • part_7_2.txt311 MB
Icon
Název
README.txt
Velikost
1.93 KB
Formát
Textový soubor
Popis
readme
MD5
a286e714b793d3a196864122183a7fa1
 Stáhnout soubor  Náhled
 Náhled souboru  
OAGKX Keyword Generation Dataset
================================

OAGKX is a keyword extraction/generation dataset consisting
of 22674436 abstracts, titles and keyword strings 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 (OAGKX Keyword 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/11234/1-3062


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

If using it, please cite the following paper:

Çano Erion, Bojar Ondřej. Keyphrase Generation: A Multi-Aspect Survey. FRUCT 2019,
Proceedings of th . . .
                                            

Zobrazit minimální záznam