Clustering is a method in machine learning that groups data based on similarities. Hierarchical clustering is a type of clustering that organizes data in a nested structure. This study looked at how well hierarchical clustering works with time series data. The researchers tested different hierarchical clustering algorithms and found that they are effective for organizing time series data both internally and externally.