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ESANN
2000
13 years 8 months ago
Distributed clustering and local regression for knowledge discovery in multiple spatial databases
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
FGCS
2007
106views more  FGCS 2007»
13 years 7 months ago
Distributed data mining services leveraging WSRF
The continuous increase of data volumes available from many sources raises new challenges for their effective understanding. Knowledge discovery in large data repositories involv...
Antonio Congiusta, Domenico Talia, Paolo Trunfio
HAIS
2009
Springer
14 years 19 hour ago
An Evolutionary Ensemble-Based Method for Rule Extraction with Distributed Data
This paper presents a methodology for knowledge discovery from inherently distributed data without moving it from its original location, completely or partially, to other locations...
Diego M. Escalante, Miguel Angel Rodriguez, Antoni...
DEXAW
2005
IEEE
133views Database» more  DEXAW 2005»
13 years 9 months ago
Inductive Databases: Towards a New Generation of Databases for Knowledge Discovery
Data mining applications are typically used in the decision making process. The Knowledge Discovery Process (KDD process for short) is a typical iterative process, in which not on...
Rosa Meo
KDD
1998
ACM
145views Data Mining» more  KDD 1998»
13 years 11 months ago
Aggregation of Imprecise and Uncertain Information for Knowledge Discovery in Databases
We consider the problem of aggregation for uncertain and imprecise data. For such data, we define aggregation operators and use them to provide information on properties and patte...
Sally I. McClean, Bryan W. Scotney, Mary Shapcott