An ensemble topic extraction approach based on optimization clusters using hybrid multi-verse optimizer for scientific publications
Author:
Funder
Universiti Sains Malaysia
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-020-02439-4.pdf
Reference95 articles.
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2. Abasi AK, Khader AT, Al-Betar MA, Naim S, Makhadmeh SN, Alyasseri ZAA (2019b) A text feature selection technique based on binary multi-verse optimizer for text clustering. In: 2019 IEEE Jordan international joint conference on electrical engineering and information technology (JEEIT), IEEE, pp 1–6
3. Abasi AK, Khader AT, Al-Betar MA, Naim S, Alyasseri ZAA, Makhadmeh SN (2020a) A novel hybrid multi-verse optimizer with k-means for text documents clustering. Neural Comput Appl. https://doi.org/10.1007/s00521-020-04945-0
4. Abasi AK, Khader AT, Al-Betar MA, Naim S, Makhadmeh SN, Alyasseri ZAA (2020b) Link-based multi-verse optimizer for text documents clustering. Applied Soft Computing 87:106002
5. Aljarah I, Mafarja M, Heidari AA, Faris H, Mirjalili S (2020) Multi-verse optimizer: theory, literature review, and application in data clustering. In: Nature-Inspired Optimizers. Springer, Berlin, pp 123–141
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