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» Approximation Algorithms for Data Placement Problems
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ICDE
2011
IEEE
207views Database» more  ICDE 2011»
12 years 11 months ago
Monte Carlo query processing of uncertain multidimensional array data
— Array database systems are architected for scientific and engineering applications. In these applications, the value of a cell is often imprecise and uncertain. There are at le...
Tingjian Ge, David Grabiner, Stanley B. Zdonik
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 1 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
DMIN
2006
144views Data Mining» more  DMIN 2006»
13 years 9 months ago
Discovering Assignment Rules in Workforce Schedules Using Data Mining
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
Jihong Yan
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 8 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
CVIU
2008
180views more  CVIU 2008»
13 years 8 months ago
Topology cuts: A novel min-cut/max-flow algorithm for topology preserving segmentation in N-D images
Topology is an important prior in many image segmentation tasks. In this paper, we design and implement a novel graph-based min-cut/max-flow algorithm that incorporates topology p...
Yun Zeng, Dimitris Samaras, Wei Chen, Qunsheng Pen...