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» Approximate Data Structures with Applications
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KDD
2005
ACM
92views Data Mining» more  KDD 2005»
16 years 7 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
KDD
2009
ACM
168views Data Mining» more  KDD 2009»
16 years 1 months ago
Cartesian contour: a concise representation for a collection of frequent sets
In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this sche...
Ruoming Jin, Yang Xiang, Lin Liu
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
16 years 1 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
ICDM
2008
IEEE
172views Data Mining» more  ICDM 2008»
16 years 1 months ago
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference
Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the ...
Steffen Rendle, Lars Schmidt-Thieme
IJCNN
2007
IEEE
16 years 1 months ago
Branching Principal Components: Elastic Graphs, Topological Grammars and Metro Maps
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...