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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 3 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
CLUSTER
2003
IEEE
14 years 3 months ago
A Cluster-Based Solution for High Performance Hmmpfam Using EARTH Execution Model
Hmmpfam is a widely used computation-intensive bioinformatics software for sequence classification. The contribution of this paper is the first largely scalable and robust clust...
Weirong Zhu, Yanwei Niu, Jizhu Lu, Chuan Shen, Gua...
CIKM
2006
Springer
13 years 11 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
BMCBI
2006
164views more  BMCBI 2006»
13 years 10 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
SIGMOD
2000
ACM
212views Database» more  SIGMOD 2000»
14 years 2 months ago
SQLEM: Fast Clustering in SQL using the EM Algorithm
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...
Carlos Ordonez, Paul Cereghini