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» Approximate data mining in very large relational data
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PODS
2004
ACM
148views Database» more  PODS 2004»
16 years 4 months ago
Deterministic Wavelet Thresholding for Maximum-Error Metrics
Several studies have demonstrated the effectiveness of the wavelet decomposition as a tool for reducing large amounts of data down to compact wavelet synopses that can be used to ...
Minos N. Garofalakis, Amit Kumar
EUROMICRO
2002
IEEE
15 years 9 months ago
Performance Tradeoffs for Static Allocation of Zero-Copy Buffers
Internet services like the world-wide web and multimedia applications like News- and Video-on-Demand have become very popular over the last years. Due to the large number of users ...
Pål Halvorsen, Espen Jorde, Karl-André...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 4 months ago
Locality sensitive hash functions based on concomitant rank order statistics
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kave Eshghi, Shyamsundar Rajaram
WSDM
2012
ACM
254views Data Mining» more  WSDM 2012»
13 years 12 months ago
Maximizing product adoption in social networks
One of the key objectives of viral marketing is to identify a small set of users in a social network, who when convinced to adopt a product will influence others in the network l...
Smriti Bhagat, Amit Goyal 0002, Laks V. S. Lakshma...
SGAI
2009
Springer
15 years 11 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