Multi-view multi-objective clustering-based framework for scientific document summarization using citation context

Author:

Saini NaveenORCID,Reddy Saichethan Miriyala,Saha Sriparna,Moreno Jose G.,Doucet Antoine

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference70 articles.

1. AbuRa’ed A, Chiruzzo L, Saggion H, Accuosto P, Bravo Serrano À (2017) Lastus/taln@ clscisumm-17: Cross-document sentence matching and scientific text summarization systems. In: BIRNDL@ SIGIR (2)

2. Aggarwal CC, Reddy CK (2014) Data clustering algorithms and application. CRC Press, Boca Raton

3. Alambo A, Lohstroh C, Madaus E, Padhee S, Foster B, Banerjee T, Thirunarayan K, Raymer M (2020) Topic-centric unsupervised multi-document summarization of scientific and news articles. arXiv:201108072

4. Beltagy I, Cohan A, Feigenblat G, Freitag D, Ghosal T, Hall K, Herrmannova D, Knoth P, Lo K, Mayr P et al (2021) Overview of the second workshop on scholarly document processing. Tech. rep. Oak Ridge National Lab.(ORNL). Oak Ridge, TN (United States)

5. Bornmann L, Mutz R (2015) Growth rates of modern science: a bibliometric analysis based on the number of publications and cited references. J Assoc Inform Sci Technol 66(11):2215–2222

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1. Optimized Text Summarization Using Abstraction and Extraction;Proceedings of Data Analytics and Management;2023

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