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» Mining discriminative items in multiple data streams
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ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
15 years 3 months ago
Sequential Pattern Mining in Multiple Streams
In this paper, we deal with mining sequential patterns in multiple data streams. Building on a state-of-the-art sequential pattern mining algorithm PrefixSpan for mining transact...
Gong Chen, Xindong Wu, Xingquan Zhu
PODS
2006
ACM
217views Database» more  PODS 2006»
15 years 9 months ago
A simpler and more efficient deterministic scheme for finding frequent items over sliding windows
In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
Lap-Kei Lee, H. F. Ting
DIS
2009
Springer
15 years 4 months ago
A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams
Some challenges in frequent pattern mining from data streams are the drift of data distribution and the computational efficiency. In this work an additional challenge is considered...
Fabio Fumarola, Anna Ciampi, Annalisa Appice, Dona...
ICDM
2008
IEEE
182views Data Mining» more  ICDM 2008»
15 years 4 months ago
Multiple-Instance Regression with Structured Data
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) op...
Kiri L. Wagstaff, Terran Lane, Alex Roper
ICDM
2003
IEEE
125views Data Mining» more  ICDM 2003»
15 years 2 months ago
Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns
The data stream captured by recording inhabitantdevice interactions in an environment can be mined to discover significant patterns, which an intelligent agent could use to automa...
Edwin O. Heierman III, Diane J. Cook