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ASC
2011
13 years 3 months ago
A rough set approach to multiple dataset analysis
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Ken Kaneiwa
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ICDE
2008
IEEE
498views Database» more  ICDE 2008»
15 years 8 months ago
Injector: Mining Background Knowledge for Data Anonymization
Existing work on privacy-preserving data publishing cannot satisfactorily prevent an adversary with background knowledge from learning important sensitive information. The main cha...
Tiancheng Li, Ninghui Li
DKE
2007
115views more  DKE 2007»
13 years 8 months ago
An improved methodology on information distillation by mining program source code
This paper presents a methodology for knowledge acquisition from source code. We use data mining to support semiautomated software maintenance and comprehension and provide practi...
Yiannis Kanellopoulos, Christos Makris, Christos T...
CINQ
2004
Springer
157views Database» more  CINQ 2004»
14 years 12 days 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