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FIMI
2003
95views Data Mining» more  FIMI 2003»
13 years 9 months ago
Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
Attila Gyenesei, Jukka Teuhola
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 7 months ago
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Michael Hahsler
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
13 years 5 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang
URBAN
2008
86views more  URBAN 2008»
13 years 7 months ago
Social area analysis, data mining, and GIS
: There is a long tradition of describing cities through a focus on the characteristics of their residents. A brief review of the history of this approach to describing cities high...
Seth E. Spielman, Jean-Claude Thill
BIODATAMINING
2008
120views more  BIODATAMINING 2008»
13 years 7 months ago
Filling the gap between biology and computer science
This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful ...
Jesús S. Aguilar-Ruiz, Jason H. Moore, Mary...