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PAKDD
2005
ACM
94views Data Mining» more  PAKDD 2005»
16 years 22 days ago
Progressive Sampling for Association Rules Based on Sampling Error Estimation
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang
KDD
2004
ACM
157views Data Mining» more  KDD 2004»
16 years 18 days ago
On detecting space-time clusters
Detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). The pioneering work on the spatial scan statistic is often use...
Vijay S. Iyengar
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 18 days ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole
PAKDD
2004
ACM
127views Data Mining» more  PAKDD 2004»
16 years 18 days ago
Exploiting Recurring Usage Patterns to Enhance Filesystem and Memory Subsystem Performance
In many cases, normal uses of a system form patterns that will repeat. The most common patterns can be collected into a prediction model which will essentially predict that usage p...
Benjamin Rutt, Srinivasan Parthasarathy
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
16 years 16 days ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel