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» Statistical Supports for Frequent Itemsets on Data Streams
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PODS
2006
ACM
134views Database» more  PODS 2006»
16 years 2 months ago
Finding global icebergs over distributed data sets
Finding icebergs ? items whose frequency of occurrence is above a certain threshold ? is an important problem with a wide range of applications. Most of the existing work focuses ...
Qi Zhao, Mitsunori Ogihara, Haixun Wang, Jun Xu
BTW
2005
Springer
104views Database» more  BTW 2005»
15 years 7 months ago
Maintaining Nonparametric Estimators over Data Streams
Abstract: An effective processing and analysis of data streams is of utmost importance for a plethora of emerging applications like network monitoring, traffic management, and fi...
Björn Blohsfeld, Christoph Heinz, Bernhard Se...
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KDD
2002
ACM
189views Data Mining» more  KDD 2002»
16 years 2 months ago
Sequential PAttern mining using a bitmap representation
We introduce a new algorithm for mining sequential patterns. Our algorithm is especially efficient when the sequential patterns in the database are very long. We introduce a novel...
Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Y...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 2 months ago
Efficient closed pattern mining in the presence of tough block constraints
In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbase...
Krishna Gade, Jianyong Wang, George Karypis
VLDB
2002
ACM
137views Database» more  VLDB 2002»
15 years 1 months ago
Comparing Data Streams Using Hamming Norms (How to Zero In)
Massive data streams are now fundamental to many data processing applications. For example, Internet routers produce large scale diagnostic data streams. Such streams are rarely s...
Graham Cormode, Mayur Datar, Piotr Indyk, S. Muthu...