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CBMS
2005
IEEE
14 years 1 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 8 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
PARMA
2004
136views Database» more  PARMA 2004»
13 years 9 months ago
Using Classification and Visualization on Pattern Databases for Gene Expression Data Analysis
Abstract. We are designing new data mining techniques on gene expression data, more precisely inductive querying techniques that extract a priori interesting bi-sets, i.e., sets of...
Céline Robardet, Ruggero G. Pensa, Jé...
IDA
2005
Springer
14 years 1 months ago
From Local Pattern Mining to Relevant Bi-cluster Characterization
Clustering or bi-clustering techniques have been proved quite useful in many application domains. A weakness of these techniques remains the poor support for grouping characterizat...
Ruggero G. Pensa, Jean-François Boulicaut
ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
13 years 5 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh