Mining Eye-Tracking Data for Text Summarization-Reference-Cited by-同舟云学术

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Mining Eye-Tracking Data for Text Summarization

Published:2023-07-21 Issue: Volume: Page:1-19
ISSN:1044-7318
Container-title:International Journal of Human–Computer Interaction
language:en
Short-container-title:International Journal of Human–Computer Interaction

Author:

Taieb-Maimon Meirav¹^ORCID,Romanovski-Chernik Aleksandr¹,Last Mark¹^ORCID,Litvak Marina²,Elhadad Michael³

Affiliation:

1. Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

2. Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva, Israel

3. Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel

Funder

the Israeli Council for Higher Education (CHE) via Data Science Research Center

Ben-Gurion University of the Negev, Israel

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics

Link

https://www.tandfonline.com/doi/pdf/10.1080/10447318.2023.2227827

Reference109 articles.

1. Allahyari, M., Pouriyeh, S., Assefi, M., Safaei, S., Trippe, E. D., Gutierrez, J. B. & Kochut, K. (2017). Text summarization techniques: A brief survey. arXiv preprint arXiv:1707.02268.

2. Perceived Self-Efficacy in Cognitive Development and Functioning

3. Aspect-Based Personalized Text Summarization

4. Bi, K., Jha, R., Croft, W. B. & Celikyilmaz, A. (2020). AREDSUM: Adaptive redundancy-aware iterative sentence ranking for extractive document summarization. arXiv preprint arXiv:2004.06176.

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