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- W2969602806 abstract "<div style=’text-align: justify;>Clustering provides a prime important role as an unsupervised learning method in data analytics to assist many real-world problems such as image segmentation, object recognition or information retrieval. It is often an issue of difficulty for traditional clustering technique due to non-optimal result exist because of the presence of outliers and noise data. This review paper provides a review of single clustering methods that were applied in various domains. The aim is to see the potential suitable applications and aspect of improvement of the methods. Three categories of single clustering methods were suggested, and it would be beneficial to the researcher to see the clustering aspects as well as to determine the requirement for clustering method for an employment based on the state of the art of the previous research findings.</div>" @default.
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- W2969602806 date "2019-12-01" @default.
- W2969602806 modified "2023-09-29" @default.
- W2969602806 title "Review of single clustering methods" @default.
- W2969602806 doi "https://doi.org/10.11591/ijai.v8.i3.pp221-227" @default.
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