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» Set cover algorithms for very large datasets
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MLDM
2009
Springer
15 years 4 months ago
PMCRI: A Parallel Modular Classification Rule Induction Framework
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
Frederic T. Stahl, Max A. Bramer, Mo Adda
SGAI
2009
Springer
15 years 4 months ago
Parallel Rule Induction with Information Theoretic Pre-Pruning
In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to indu...
Frederic T. Stahl, Max Bramer, Mo Adda
PAMI
2010
164views more  PAMI 2010»
14 years 8 months ago
Large-Scale Discovery of Spatially Related Images
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Ondrej Chum, Jiri Matas
WEBDB
2007
Springer
128views Database» more  WEBDB 2007»
15 years 3 months ago
Supporting Range Queries on Web Data Using k-Nearest Neighbor Search
A large volume of geospatial data is available on the web through various forms of applications. However, access to these data is limited by certain types of queries due to restric...
Wan D. Bae, Shayma Alkobaisi, Seon Ho Kim, Sada Na...
SDM
2009
SIAM
343views Data Mining» more  SDM 2009»
15 years 7 months ago
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
Masashi Sugiyama, Yoshinobu Kawahara