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» Approximate data mining in very large relational data
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VLDB
2005
ACM
136views Database» more  VLDB 2005»
15 years 7 months ago
On k-Anonymity and the Curse of Dimensionality
In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed fo...
Charu C. Aggarwal
ICDM
2009
IEEE
155views Data Mining» more  ICDM 2009»
15 years 8 months ago
Stacked Gaussian Process Learning
—Triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utili...
Marion Neumann, Kristian Kersting, Zhao Xu, Daniel...
KDD
2007
ACM
186views Data Mining» more  KDD 2007»
16 years 2 months ago
Content-based document routing and index partitioning for scalable similarity-based searches in a large corpus
We present a document routing and index partitioning scheme for scalable similarity-based search of documents in a large corpus. We consider the case when similarity-based search ...
Deepavali Bhagwat, Kave Eshghi, Pankaj Mehra
CIKM
1999
Springer
15 years 6 months ago
Requirement-Based Data Cube Schema Design
On-line analytical processing (OLAP) requires e cient processing of complex decision support queries over very large databases. It is well accepted that pre-computed data cubes ca...
David Wai-Lok Cheung, Bo Zhou, Ben Kao, Hongjun Lu...
TNN
2008
182views more  TNN 2008»
15 years 1 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...