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» Identifying Clusters from Positive Data
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BIBE
2005
IEEE
154views Bioinformatics» more  BIBE 2005»
15 years 3 months ago
Effective Pre-Processing Strategies for Functional Clustering of a Protein-Protein Interactions Network
In this article we present novel preprocessing techniques, based on topological measures of the network, to identify clusters of proteins from Protein-protein interaction (PPI) ne...
Duygu Ucar, Srinivasan Parthasarathy, Sitaram Asur...
81
Voted
ISMIS
2009
Springer
15 years 4 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
WWW
2009
ACM
13 years 5 months ago
The slashdot zoo: mining a social network with negative edges
We analyse the corpus of user relationships of the Slashdot technology news site. The data was collected from the Slashdot Zoo feature where users of the website can tag other user...
J. Kunegis, A. Lomatzsch, and C. Bauckhage
CSDA
2008
128views more  CSDA 2008»
14 years 9 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
78
Voted
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
15 years 4 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...