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» Clustering by pattern similarity in large data sets
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ICDM
2003
IEEE
100views Data Mining» more  ICDM 2003»
14 years 28 days ago
Tractable Group Detection on Large Link Data Sets
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
ICDE
2011
IEEE
233views Database» more  ICDE 2011»
12 years 11 months ago
Answering approximate string queries on large data sets using external memory
— An approximate string query is to find from a collection of strings those that are similar to a given query string. Answering such queries is important in many applications su...
Alexander Behm, Chen Li, Michael J. Carey
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
14 years 29 days ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
CIKM
2009
Springer
14 years 2 months ago
Maximal metric margin partitioning for similarity search indexes
We propose a partitioning scheme for similarity search indexes that is called Maximal Metric Margin Partitioning (MMMP). MMMP divides the data on the basis of its distribution pat...
Hisashi Kurasawa, Daiji Fukagawa, Atsuhiro Takasu,...
INCDM
2010
Springer
486views Data Mining» more  INCDM 2010»
13 years 9 months ago
Finding Temporal Patterns in Noisy Longitudinal Data: A Study in Diabetic Retinopathy
This paper describes an approach to temporal pattern mining using the concept of user de ned temporal prototypes to de ne the nature of the trends of interests. The temporal patt...
Vassiliki Somaraki, Deborah Broadbent, Frans Coene...