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ADMA
2009
Springer
186views Data Mining» more  ADMA 2009»
14 years 3 months ago
Mining Compressed Repetitive Gapped Sequential Patterns Efficiently
Mining frequent sequential patterns from sequence databases has been a central research topic in data mining and various efficient mining sequential patterns algorithms have been p...
Yongxin Tong, Zhao Li, Dan Yu, Shilong Ma, Zhiyuan...
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
13 years 8 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...
ICDE
2009
IEEE
173views Database» more  ICDE 2009»
13 years 6 months ago
Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database
There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to ...
Bolin Ding, David Lo, Jiawei Han, Siau-Cheng Khoo
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
14 years 23 days ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh
TSDM
2000
151views Data Mining» more  TSDM 2000»
14 years 3 days ago
Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events
The novel Time Series Data Mining (TSDM) framework is applied to analyzing financial time series. The TSDM framework adapts and innovates data mining concepts to analyzing time ser...
Richard J. Povinelli