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» Relational peculiarity-oriented mining
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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
14 years 10 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
KDD
2006
ACM
157views Data Mining» more  KDD 2006»
14 years 10 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
KDD
2005
ACM
137views Data Mining» more  KDD 2005»
14 years 10 months ago
Pattern-based similarity search for microarray data
One fundamental task in near-neighbor search as well as other similarity matching efforts is to find a distance function that can efficiently quantify the similarity between two o...
Haixun Wang, Jian Pei, Philip S. Yu
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 10 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
14 years 4 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...