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» DISC: Data-Intensive Similarity Measure for Categorical Data
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PAKDD
2011
ACM
419views Data Mining» more  PAKDD 2011»
12 years 7 months ago
DISC: Data-Intensive Similarity Measure for Categorical Data
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
Aditya Desai, Himanshu Singh, Vikram Pudi
SDM
2008
SIAM
158views Data Mining» more  SDM 2008»
13 years 5 months ago
Similarity Measures for Categorical Data: A Comparative Evaluation
Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relative...
Shyam Boriah, Varun Chandola, Vipin Kumar
JMLR
2008
148views more  JMLR 2008»
13 years 4 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
13 years 9 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
BMCBI
2007
135views more  BMCBI 2007»
13 years 4 months ago
Measuring similarities between gene expression profiles through new data transformations
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...