Parsing AUC Result-Figures in Machine Learning Specific Scholarly Documents for Semantically-enriched Summarization-Reference-Cited by-同舟云学术

Parsing AUC Result-Figures in Machine Learning Specific Scholarly Documents for Semantically-enriched Summarization

Published:2021-11-14 Issue: Volume: Page:1-27
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Safder Iqra¹,Batool Hafsa¹,Sarwar Raheem²,Zaman Farooq¹,Aljohani Naif Radi³^ORCID,Nawaz Raheel⁴,Gaber Mohamed⁵,Hassan Saeed-Ul⁶^ORCID

Affiliation:

1. Department of Computer Science, Information Technology University, Lahore, Pakistan

2. Research Group in Computational Linguistics, Research Institute of Information and Language Processing, University of Wolverhampton, Wolverhampton, UK

3. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

4. Department of Operations, Technology, Events and Hospitality Management, Manchester Metropolitan University, Manchester, UK

5. Big Data Analytics, School of Computing and Digital Technology, Birmingham City University, Birmingham, UK

6. Department of Computing and Mathematics, Management, Manchester Metropolitan University, Manchester, UK

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2021.2004347

Reference58 articles.

1. NATSUM: Narrative abstractive summarization through cross-document timeline generation

2. Summarizing figures, tables, and algorithms in scientific publications to augment search results

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