Hierarchical clustering is a method used to group data in a tree-like structure. This technique helps organize complex datasets by clustering similar data together. The main focus is on improving the accuracy of these clusters by enhancing the relationships between attributes. The researchers suggest that agglomerative clustering is the preferred method for this task. By refining the relationships between attributes, the accuracy of the clustering process can be significantly improved.