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» SSM : A Frequent Sequential Data Stream Patterns Miner
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KDD
2012
ACM
217views Data Mining» more  KDD 2012»
11 years 10 months ago
The long and the short of it: summarising event sequences with serial episodes
An ideal outcome of pattern mining is a small set of informative patterns, containing no redundancy or noise, that identifies the key structure of the data at hand. Standard freq...
Nikolaj Tatti, Jilles Vreeken
KDD
2007
ACM
151views Data Mining» more  KDD 2007»
14 years 8 months ago
Efficient mining of iterative patterns for software specification discovery
Studies have shown that program comprehension takes up to 45% of software development costs. Such high costs are caused by the lack-of documented specification and further aggrava...
Chao Liu 0001, David Lo, Siau-Cheng Khoo
SAC
2004
ACM
14 years 1 months ago
A new algorithm for gap constrained sequence mining
The sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. Several application domains require limiting the maximum tempor...
Salvatore Orlando, Raffaele Perego, Claudio Silves...
EUROSYS
2007
ACM
14 years 4 months ago
Competitive prefetching for concurrent sequential I/O
During concurrent I/O workloads, sequential access to one I/O stream can be interrupted by accesses to other streams in the system. Frequent switching between multiple sequential ...
Chuanpeng Li, Kai Shen, Athanasios E. Papathanasio...
ICMCS
2009
IEEE
199views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Association rule mining in multiple, multidimensional time series medical data
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Gaurav N. Pradhan, B. Prabhakaran