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» Online Data Mining for Co-Evolving Time Sequences
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PAKDD
2010
ACM
189views Data Mining» more  PAKDD 2010»
15 years 2 months ago
Subsequence Matching of Stream Synopses under the Time Warping Distance
In this paper, we propose a method for online subsequence matching between histogram-based stream synopsis structures under the dynamic warping distance. Given a query synopsis pat...
Su-Chen Lin, Mi-Yen Yeh, Ming-Syan Chen
EUROCAST
2005
Springer
133views Hardware» more  EUROCAST 2005»
15 years 3 months ago
An Iterative Method for Mining Frequent Temporal Patterns
The incorporation of temporal semantic into the traditional data mining techniques has caused the creation of a new area called Temporal Data Mining. This incorporation is especial...
Francisco Guil, Antonio B. Bailón, Alfonso ...
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
15 years 10 months ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà
111
Voted
ICDE
2005
IEEE
176views Database» more  ICDE 2005»
15 years 3 months ago
LAPIN-SPAM: An Improved Algorithm for Mining Sequential Pattern
Sequence pattern mining is an important research problem because it is the basis of many other applications. Yet how to efficiently implement the mining is difficult due to the ...
Zhenglu Yang, Masaru Kitsuregawa
ICDM
2006
IEEE
153views Data Mining» more  ICDM 2006»
15 years 4 months ago
k-STARs: Sequences of Spatio-Temporal Association Rules
A Spatio-Temporal Association Rule (STAR) describes how objects move between regions over time. Since they describe only a single movement between two regions, it is very difficu...
Florian Verhein