The article explores ways to make clustering algorithms better by using prior knowledge to group data more effectively. By improving hierarchical clustering methods with new techniques, researchers aim to uncover more useful information from the data being analyzed. Most current methods focus on partitional clustering, but there is a need for more research on hierarchical clustering. The goal is to enhance the performance of clustering algorithms by incorporating knowledge-based constraints.