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» Mining data streams with periodically changing distributions
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PAKDD
2007
ACM
144views Data Mining» more  PAKDD 2007»
14 years 2 months ago
Approximately Mining Recently Representative Patterns on Data Streams
Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
Jia-Ling Koh, Yuan-Bin Don
DAWAK
2006
Springer
14 years 12 days 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
SSDBM
2006
IEEE
133views Database» more  SSDBM 2006»
14 years 2 months ago
An Extensible Infrastructure for Processing Distributed Geospatial Data Streams
Although the processing of data streams has been the focus of many research efforts in several areas, the case of remotely sensed streams in scientific contexts has received less...
Carlos Rueda, Michael Gertz, Bertram Ludäsche...
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
14 years 10 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
14 years 9 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