Incremental Constrained Clustering

Incremental Constrained Clustering is an interactive clustering method that improves the basic partitioning of a dataset by gradually adding constraints. The goal of this approach is to guide the clustering process towards the desired target through user feedback on the continuously generated clustering results, thereby obtaining more accurate and representative data divisions. This method has significant application value in handling complex data structures and domain-specific knowledge, effectively enhancing the quality and practicality of clustering.