The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A new feature selection method to improve the document clustering using particle swarm optimization algorithm
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Citations
Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
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Albashish, D., Hammouri, A. I., Braik, M., Atwan, J., & Sahran, S. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2020.107026 · Cited by 154
A layer-by-layer quality monitoring framework for 3D printing
Najjartabar Bisheh, M., Chang, S. I., & Lei, S. (2021) · Computers & Industrial Engineering · doi:10.1016/j.cie.2021.107314 · Cited by 58
A hybrid quantum feature selection algorithm using a quantum inspired graph theoretic approach
Chakraborty, S., Shaikh, S. H., Chakrabarti, A., & Ghosh, R. (2020) · Applied Intelligence · doi:10.1007/s10489-019-01604-3 · Cited by 51
Metadata
- Authors
- Abualigah, L. M., Khader, A. T., & Hanandeh, E. S.
- Venue
- Journal of Computational Science
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 25
- Pages
- 456-466
- ISSN
- 1877-7503 (ISSN-L)
- OpenAlex
- W2753434909
- Cited by
- 480
- References
- 1
- FWCI
- 32.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A new feature selection method to improve the document clustering using particle swarm optimization algorithm. https://app.cochat.ai/papers/10.1016/j.jocs.2017.07.018
- The paper
- Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2018). A new feature selection method to improve the document clustering using particle swarm optimization algorithm. Journal of Computational Science. https://doi.org/10.1016/j.jocs.2017.07.018
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
