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» Efficient frequent pattern mining over data streams
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PVLDB
2010
134views more  PVLDB 2010»
14 years 8 months ago
High-Performance Dynamic Pattern Matching over Disordered Streams
Current pattern-detection proposals for streaming data recognize the need to move beyond a simple regular-expression model over strictly ordered input. We continue in this directi...
Badrish Chandramouli, Jonathan Goldstein, David Ma...
SIGMOD
2005
ACM
135views Database» more  SIGMOD 2005»
15 years 9 months ago
Mining data streams: a review
The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously an...
Mohamed Medhat Gaber, Arkady B. Zaslavsky, Shonali...
CIDM
2007
IEEE
15 years 4 months ago
Structure Prediction in Temporal Networks using Frequent Subgraphs
— There are several types of processes which can be modeled explicitly by recording the interactions between a set of actors over time. In such applications, a common objective i...
Mayank Lahiri, Tanya Y. Berger-Wolf
ICTAI
2003
IEEE
15 years 2 months ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
PODS
2009
ACM
134views Database» more  PODS 2009»
15 years 10 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...