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KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 9 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
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...
Jens-Peter Dittrich, Bernhard Seeger
KAIS
2000
87views more  KAIS 2000»
13 years 8 months ago
An Index Structure for Data Mining and Clustering
Abstract. In this paper we present an index structure, called MetricMap, that takes a set of objects and a distance metric and then maps those objects to a k-dimensional space in s...
Xiong Wang, Jason Tsong-Li Wang, King-Ip Lin, Denn...
AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
14 years 2 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
BMCBI
2011
13 years 3 days ago
MINE: Module Identification in NEtworks
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
Kahn Rhrissorrakrai, Kristin C. Gunsalus
SAC
2008
ACM
13 years 8 months ago
Mining fault-tolerant frequent patterns efficiently with powerful pruning
The mining of frequent patterns in databases has been studied for several years. However, the real-world data tends to be dirty and frequent pattern mining which extracts patterns...
Jhih-Jie Zeng, Guanling Lee, Chung-Chi Lee