OAGS Title Generation Dataset

  Authors

Çano, Erion

  Item identifier

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

 Date issued

2019-09

 Type

corpus

 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)

 Acknowledgement

European Union and the Czech Ministry of Education

Project code: CZ.02.2.69/0.0/0.0/16_027/0008495

Project name: International Mobility of of Researchers at Charles University

 Subject(s)

Title Generation Dataset Abstractive Text Summarization Scientific Papers Corpus

 Collection(s)

LINDAT / CLARIN Data & Tools

 

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

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