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» Mining Very Large Databases
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SISAP
2009
IEEE
134views Data Mining» more  SISAP 2009»
14 years 4 months ago
Searching by Similarity and Classifying Images on a Very Large Scale
—In the demonstration we will show a system for searching by similarity and automatically classifying images in a very large dataset. The demonstrated techniques are based on the...
Giuseppe Amato, Pasquale Savino
ICDE
2010
IEEE
491views Database» more  ICDE 2010»
14 years 9 months ago
TrajStore: An Adaptive Storage System for Very Large Trajectory Data Sets
The rise of GPS and broadband-speed wireless devices has led to tremendous excitement about a range of applications broadly characterized as "location based services". Cu...
Philippe Cudré-Mauroux, Eugene Wu, Samuel M...
VLDB
1999
ACM
159views Database» more  VLDB 1999»
14 years 2 months ago
Aggregation Algorithms for Very Large Compressed Data Warehouses
Many efficient algorithms to compute multidimensional aggregation and Cube for relational OLAP have been developed. However, to our knowledge, there is nothing to date in the lite...
Jianzhong Li, Doron Rotem, Jaideep Srivastava
EDBT
2004
ACM
94views Database» more  EDBT 2004»
14 years 10 months ago
Mining Extremely Skewed Trading Anomalies
Trading surveillance systems screen and detect anomalous trades of equity, bonds, mortgage certificates among others. This is to satisfy federal trading regulations as well as to p...
Wei Fan, Philip S. Yu, Haixun Wang
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 10 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...