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PAKDD
2009
ACM
87views Data Mining» more  PAKDD 2009»
16 years 25 days ago
Application-Independent Feature Construction from Noisy Samples
When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
Dominique Gay, Nazha Selmaoui, Jean-Françoi...
CIB
2004
57views more  CIB 2004»
15 years 5 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
ICDM
2006
IEEE
113views Data Mining» more  ICDM 2006»
16 years 3 days ago
Mining Maximal Generalized Frequent Geographic Patterns with Knowledge Constraints
In frequent geographic pattern mining a large amount of patterns is well known a priori. This paper presents a novel approach for mining frequent geographic patterns without assoc...
Vania Bogorny, João Francisco Valiati, Sand...
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ICDM
2002
IEEE
178views Data Mining» more  ICDM 2002»
15 years 11 months ago
gSpan: Graph-Based Substructure Pattern Mining
We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining), which...
Xifeng Yan, Jiawei Han
SDM
2012
SIAM
293views Data Mining» more  SDM 2012»
13 years 8 months ago
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising
One practical inconvenience in frequent pattern mining is that it often yields a flood of common or uninformative patterns, and thus we should carefully adjust the minimum suppor...
Yoshitaka Kameya, Taisuke Sato