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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2005
ACM
86views Data Mining» more  KDD 2005»
16 years 7 months ago
Probabilistic workflow mining
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...
Ricardo Silva, Jiji Zhang, James G. Shanahan
BIODATAMINING
2008
130views more  BIODATAMINING 2008»
15 years 6 months ago
Uncovering mechanisms of transcriptional regulations by systematic mining of cis regulatory elements with gene expression profil
Background: Contrary to the traditional biology approach, where the expression patterns of a handful of genes are studied at a time, microarray experiments enable biologists to st...
Qicheng Ma, Gung-Wei Chirn, Joseph D. Szustakowski...
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
16 years 7 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
INFOSCALE
2006
ACM
16 years 22 days ago
PENS: an algorithm for density-based clustering in peer-to-peer systems
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
PKDD
2010
Springer
166views Data Mining» more  PKDD 2010»
15 years 5 months ago
A Cluster-Level Semi-supervision Model for Interactive Clustering
Abstract. Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper...
Avinava Dubey, Indrajit Bhattacharya, Shantanu God...