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KDD
2007
ACM
165views Data Mining» more  KDD 2007»
14 years 8 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
DKE
2008
79views more  DKE 2008»
13 years 7 months ago
Extracting k most important groups from data efficiently
We study an important data analysis operator, which extracts the k most important groups from data (i.e., the k groups with the highest aggregate values). In a data warehousing co...
Man Lung Yiu, Nikos Mamoulis, Vagelis Hristidis
BMCBI
2008
120views more  BMCBI 2008»
13 years 7 months ago
Statistical issues in the analysis of Illumina data
Background: Illumina bead-based arrays are becoming increasingly popular due to their high degree of replication and reported high data quality. However, little attention has been...
Mark J. Dunning, Nuno L. Barbosa-Morais, Andy G. L...
ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall