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ICDE
2010
IEEE
750views Database» more  ICDE 2010»
15 years 2 months ago
Efficient and accurate discovery of patterns in sequence datasets
Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require effici...
Avrilia Floratou, Sandeep Tata, Jignesh M. Patel
CIKM
2006
Springer
15 years 1 months ago
TRIPS and TIDES: new algorithms for tree mining
Recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. In this paper, we address the problem of...
Shirish Tatikonda, Srinivasan Parthasarathy, Tahsi...
AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
15 years 4 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...
PKDD
2005
Springer
153views Data Mining» more  PKDD 2005»
15 years 3 months ago
A Quantitative Comparison of the Subgraph Miners MoFa, gSpan, FFSM, and Gaston
Abstract. Several new miners for frequent subgraphs have been published recently. Whereas new approaches are presented in detail, the quantitative evaluations are often of limited ...
Marc Wörlein, Thorsten Meinl, Ingrid Fischer,...
KDD
2006
ACM
109views Data Mining» more  KDD 2006»
15 years 10 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han