Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...

Abstract: This paper presents a new method that combines deep k-means clustering with granule mining approaches to utilise contextual information for improving outlier detection and classification.

Billionaire entrepreneur Mark Cuban cautioned that social media algorithms, rather than candidates' policies or personalities, could have the greatest influence on voter behavior in the upcoming 2026 ...

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