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JCP
2008
104views more  JCP 2008»
14 years 10 months ago
Discovery of Sequential Patterns Coinciding with Analysts' Interests
This paper proposes a new sequential pattern mining method. The method introduces a new evaluation criterion satisfying the Apriori property. The criterion is calculated by the fre...
Shigeaki Sakurai, Youichi Kitahara, Ryohei Orihara...
ICDE
2012
IEEE
208views Database» more  ICDE 2012»
13 years 16 days ago
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
—Traditional clustering algorithms identify just a single clustering of the data. Today’s complex data, however, allow multiple interpretations leading to several valid groupin...
Emmanuel Müller, Stephan Günnemann, Ines...
IADIS
2004
14 years 11 months ago
Discovering data dependencies in Web content mining
Web content mining opens up the possibility to use data presented in web pages for the discovery of interesting and useful patterns. Our web mining tool, FBL (Filtered Bayesian Le...
José Carlos Cortizo, J. Ignacio Girá...
SIGKDD
2010
126views more  SIGKDD 2010»
14 years 4 months ago
MultiClust 2010: discovering, summarizing and using multiple clusterings
Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy
94
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PVLDB
2008
127views more  PVLDB 2008»
14 years 9 months ago
Discovering data quality rules
Dirty data is a serious problem for businesses leading to incorrect decision making, inefficient daily operations, and ultimately wasting both time and money. Dirty data often ari...
Fei Chiang, Renée J. Miller