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CINQ
2004
Springer
157views Database» more  CINQ 2004»
13 years 11 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
AMW
2010
13 years 9 months ago
Robust Clustering of Data Streams using Incremental Optimization
Discovering the patterns in evolving data streams is a very important and challenging task. In many applications, it is useful to detect the dierent patterns evolving over time and...
Basheer Hawwash, Olfa Nasraoui
ICDM
2003
IEEE
114views Data Mining» more  ICDM 2003»
14 years 1 months ago
Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis
A significant portion of knowledge discovery and data mining research focuses on finding patterns of interest in data. Once a pattern is found, it can be used to recognize satisfy...
Shou-de Lin, Hans Chalupsky
SDM
2011
SIAM
223views Data Mining» more  SDM 2011»
12 years 10 months ago
Characterizing Uncertain Data using Compression
Motivated by sensor networks, mobility data, biology and life sciences, the area of mining uncertain data has recently received a great deal of attention. While various papers hav...
Francesco Bonchi, Matthijs van Leeuwen, Antti Ukko...
WOA
2010
13 years 5 months ago
Classification of Whereabouts Patterns From Large-scale Mobility Data
Classification of users' whereabouts patterns is important for many emerging ubiquitous computing applications. Latent Dirichlet Allocation (LDA) is a powerful mechanism to e...
Laura Ferrari, Marco Mamei