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BMCBI
2010
151views more  BMCBI 2010»
13 years 8 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 2 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
CAINE
2009
13 years 6 months ago
Clustering Customer Transactions: A Rough Set Based Approach
An efficient customer behavior analysis is important for good Recommender System. Customer transaction clustering is usually the first step towards the analysis of customer behavi...
Arunava Saha, Darsana Das, Dipanjan Karmakar, Dili...
ICDM
2002
IEEE
122views Data Mining» more  ICDM 2002»
14 years 1 months ago
Using Category-Based Adherence to Cluster Market-Basket Data
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
14 years 1 months 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...