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» Mining Multiple Large Databases
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ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
14 years 3 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
ICCS
2007
Springer
14 years 4 months ago
Pushing Frequency Constraint to Utility Mining Model
Traditional association rules mining (ARM) only concerns the frequency of itemsets, which may not bring large amount of profit. Utility mining only focuses on itemsets with high ut...
Jing Wang, Ying Liu, Lin Zhou, Yong Shi, Xingquan ...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 10 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
KDD
2000
ACM
222views Data Mining» more  KDD 2000»
14 years 1 months ago
Interactive exploration of very large relational datasets through 3D dynamic projections
The grand tour, one of the most popular methods for multidimensional data exploration, is based on orthogonally projecting multidimensional data to a sequence of lower dimensional...
Li Yang
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 10 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han