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» Techniques of Cluster Algorithms in Data Mining
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VLDB
1994
ACM
140views Database» more  VLDB 1994»
15 years 1 months ago
Efficient and Effective Clustering Methods for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering ...
Raymond T. Ng, Jiawei Han
121
Voted
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
15 years 1 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
SIGKDD
2000
95views more  SIGKDD 2000»
14 years 9 months ago
Scalability for Clustering Algorithms Revisited
This paper presents a simple new algorithm that performs k-means clustering in one scan of a dataset, while using a bu er for points from the dataset of xed size. Experiments show...
Fredrik Farnstrom, James Lewis, Charles Elkan
ICDM
2006
IEEE
145views Data Mining» more  ICDM 2006»
15 years 3 months ago
Stability Region Based Expectation Maximization for Model-based Clustering
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 1 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...