Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopul...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...