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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 7 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
IJDMMM
2008
72views more  IJDMMM 2008»
15 years 6 months ago
Mining event histories: a social science perspective
We explore how recent data-mining-based tools developed in domains such as biomedicine or text-mining for extracting interesting knowledge from sequence data could be applied to pe...
Gilbert Ritschard, Alexis Gabadinho, Nicolas S. M&...
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
15 years 10 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...
AISS
2010
171views more  AISS 2010»
15 years 1 months ago
An Investigation into Influence Factor of Student Programming Grade Using Association Rule Mining
Computer programming is one of the most essential skills which each graduate has to acquire. However, there are reports that they are unable to write a program well. Researches in...
Mohamad Farhan Mohamad Mohsin, Mohd Helmy Abd Waha...
KDD
2006
ACM
167views Data Mining» more  KDD 2006»
16 years 7 months ago
Clustering pair-wise dissimilarity data into partially ordered sets
Ontologies represent data relationships as hierarchies of possibly overlapping classes. Ontologies are closely related to clustering hierarchies, and in this article we explore th...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...