Incremental Clustering Algorithm Based on K-Medoids
Xingjie Feng · Jisuanji gongcheng · 2005
Clustering ,in data mining ,is useful for discovering groups and identifying interesting distributions in the underlying data. There are many algorithms proposed for clustering. However,very little work is done on incremental clustering. When updates are collected and applied to the databases ,then,all patterns derived from the databases by some data mining algorithm have to be updated as well. Due to the very large size of the databases,it is highly desirable to perform these updates incrementally. This paper presents an efficient incremental clustering algorithm based on K-Medoids.