21 search results - page 1 / 5 » GESS: a scalable similarity-join algorithm for mining large ... |
KDD
2001
ACM
14 years 4 months ago
2001
ACM
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...
SIGMOD
2001
ACM
14 years 4 months ago
2001
ACM
The similarity join is an important database primitive which has been successfully applied to speed up applications such as similarity search, data analysis and data mining. The s...
ICDM
2002
IEEE
13 years 9 months ago
2002
IEEE
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...
CIDM
2007
IEEE
13 years 11 months ago
2007
IEEE
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...
CCGRID
2010
IEEE
13 years 5 months ago
2010
IEEE
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...