Hybrid method for text summarization based on statistical and semantic treatment
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-10613-9.pdf
Reference60 articles.
1. Afsharizadeh M, Ebrahimpour-Komleh H, Bagheri A (2018) Query-oriented text summarization using sentence extraction technique. 2018 4th International Conference on Web Research (ICWR). https://doi.org/10.1109/icwr.2018.8387248
2. Alami N, Meknassi M, Alaoui Ouatik S, Ennahnahi N (2015) Arabic text summarization based on graph theory. In: 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), Marrakech, pp 1–8. https://doi.org/10.1109/aiccsa.2015.7507254
3. Alami N, En-nahnahi N, Ouatik SA, Meknassi M (2018) Using unsupervised deep learning for automatic summarization of Arabic documents. Arab J Sci Eng 43(12):7803–7815
4. Alami N, Meknassi M, En-nahnahi N (2019) Enhancing unsupervised neural networks based text summarization with word embedding and ensemble learning. Expert Syst Appl 123:195–211
5. Alguliyev RM, Aliguliyev RM, Isazade NR (2015) An unsupervised approach to generating generic summaries of documents. Appl Soft Comput 34:236–250
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