OAGS Title Generation Dataset

Name: OAGS Title Generation Dataset
License: http://creativecommons.org/licenses/by/4.0/

Çano, Erion

OAGS Title Generation Dataset

LINDAT / CLARIAH-CZ

Authors: Çano, Erion

Item identifier: http://hdl.handle.net/11234/1-3043

Referenced by: https://www.aclweb.org/anthology/W19-8630/

Date issued: 2019-09

Type: corpus, text

Size: 34993700 entries, 7 files, 46.8 gb, 14.8 gb

Language(s): English

Description: OAGS is a title generation dataset consisting of 34993700 abstracts and titles from scientific 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. The data is derived from OAG data collection (https://aminer.org/open-academic-graph) which was released under ODC-BY licence. This data (OAGS Title 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, "Efficiency Metrics for Data-Driven Models: A Text Summarization Case Study", INLG 2019, The 12th International Conference on Natural Language Generation, November 2019, Tokyo, Japan. To reproduce the experiments in the above paper, you can use oags_train1.txt, oags_train2.txt, oags_train3.txt, oags_test.txt and oags_val.txt files. If you need more data samples you can get them from oags_train_backup.txt and oags_val-test_backup.txt.

Publisher: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)

Subject(s): Title Generation Dataset Abstractive Text Summarization Scientific Papers Corpus

Collection(s): LINDAT / CLARIAH-CZ Data & Tools

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http://hdl.handle.net/11234/1-3079

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OAGS Title Generation Dataset
===============================

OAGS is a title generation dataset consisting of 34993700 abstracts 
and titles from scientific 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. 

The data is derived from OAG data collection 
(https://aminer.org/open-academic-graph) which was released 
under ODC-BY licence. 

This data (OAGS Title Generation Dataset) is released under 
CC-BY licence (https://creativecommons.org/licenses/by/4.0/). 


Download
--------

This dataset can be download from LINDAT/CLARIN repository
http://hdl.handle.net/11234/1-3043


Publications
------------

If using it, please cite the following paper:

Çano, Erion and Bojar, Ondřej, 2019, "Efficiency Metrics for 
Data-Driven Models: A Text Summarization Case Study", INLG 2019, 
The 12th Inter . . .

Name: OAGS.zip
Size: 14.89 GB
Format: application/zip
Description: Data
MD5: b3def7c79f11d2c109c48cc0a72b88ae

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OAGS
- oags_train3.txt1 GB
- oags_val.txt14 MB
- oags_val-test_backup.txt657 MB
- oags_train2.txt1 GB
- oags_test.txt14 MB
- oags_train_backup.txt42 GB
- oags_train1.txt557 MB

OAGS Title Generation Dataset

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