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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 10 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
DAWAK
2006
Springer
15 years 8 months ago
An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams
Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that ...
Jia-Ling Koh, Shu-Ning Shin
SIAMIS
2010
171views more  SIAMIS 2010»
14 years 12 months ago
Global Optimization for One-Dimensional Structure and Motion Problems
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the scene is modeled as a 2D plane, and the camera sensor produces 1D images of the s...
Olof Enqvist, Fredrik Kahl, Carl Olsson, Kalle &Ar...
ICDE
2006
IEEE
158views Database» more  ICDE 2006»
16 years 6 months ago
Space-efficient Relative Error Order Sketch over Data Streams
We consider the problem of continuously maintaining order sketches over data streams with a relative rank error guarantee . Novel space-efficient and one-scan randomised technique...
Ying Zhang, Xuemin Lin, Jian Xu, Flip Korn, Wei Wa...
ICDE
2008
IEEE
135views Database» more  ICDE 2008»
16 years 6 months ago
Online Filtering, Smoothing and Probabilistic Modeling of Streaming data
In this paper, we address the problem of extending a relational database system to facilitate efficient real-time application of dynamic probabilistic models to streaming data. he ...
Bhargav Kanagal, Amol Deshpande