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» Mining Quantitative Associations in Large Database
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ICDM
2006
IEEE
127views Data Mining» more  ICDM 2006»
14 years 3 months ago
Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions
There is a need to develop methods to automatically incorporate prior knowledge to support the prediction and validation of novel functional associations. One such important sourc...
Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivi...
KYOTODL
2000
140views more  KYOTODL 2000»
13 years 11 months ago
Text Data Mining: Discovery of Important Keywords in the Cyberspace
This paper describes applications of the optimized pattern discover),framework to text and Webmining. In particular; we introduce a class of simple combinatorialpatterns over phra...
Hiroki Arimura, Jun-ichiro Abe, Hiroshi Sakamoto, ...
KDD
2004
ACM
160views Data Mining» more  KDD 2004»
14 years 10 months ago
k-TTP: a new privacy model for large-scale distributed environments
Secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. Theoretical results [2] provide a gen...
Bobi Gilburd, Assaf Schuster, Ran Wolff
PKDD
2005
Springer
110views Data Mining» more  PKDD 2005»
14 years 3 months ago
k-Anonymous Patterns
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
ADBIS
2007
Springer
143views Database» more  ADBIS 2007»
14 years 4 months ago
Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
Rayner Alfred, Dimitar Kazakov