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KDD
2008
ACM
217views Data Mining» more  KDD 2008»
10 years 10 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
10 years 10 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
ICDM
2009
IEEE
145views Data Mining» more  ICDM 2009»
9 years 7 months ago
Significance of Episodes Based on Minimal Windows
Discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. Traditionally, a level-wise approach is used to discover all frequent epis...
Nikolaj Tatti
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
9 years 9 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
FLAIRS
2007
10 years 1 days ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
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