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ICDM
2009
IEEE
145views Data Mining» more  ICDM 2009»
13 years 10 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»
14 years 10 days 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...
IS
2008
14 years 13 days ago
Efficient mining of frequent episodes from complex sequences
Discovering patterns with highly significance is an important problem in data mining discipline. An episode is defined to be a partially ordered set of events for a consecutive an...
Kuo-Yu Huang, Chia-Hui Chang
IDA
2009
Springer
14 years 7 months ago
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
Francisco Martínez-Álvarez, Alicia T...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
15 years 25 days 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