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» Approximate data mining in very large relational data
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KDD
2006
ACM
143views Data Mining» more  KDD 2006»
16 years 2 months ago
Algorithms for discovering bucket orders from data
Ordering and ranking items of different types are important tasks in various applications, such as query processing and scientific data mining. A total order for the items can be ...
Aristides Gionis, Heikki Mannila, Kai Puolamä...
WWW
2009
ACM
16 years 2 months ago
Triplify: light-weight linked data publication from relational databases
In this paper we present Triplify ? a simplistic but effective approach to publish Linked Data from relational databases. Triplify is based on mapping HTTP-URI requests onto relat...
Sören Auer, Sebastian Dietzold, Jens Lehmann,...
AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
15 years 7 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
APPT
2005
Springer
15 years 7 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk
BIRD
2008
Springer
141views Bioinformatics» more  BIRD 2008»
15 years 3 months ago
Nested q-Partial Graphs for Genetic Network Inference from "Small n, Large p" Microarray Data
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
Kevin Kontos, Gianluca Bontempi