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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 10 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
DAWAK
2008
Springer
13 years 11 months ago
Mining Serial Episode Rules with Time Lags over Multiple Data Streams
The problem of discovering episode rules from static databases has been studied for years due to its wide applications in prediction. In this paper, we make the first attempt to st...
Tung-Ying Lee, En Tzu Wang, Arbee L. P. Chen
IJAR
2011
118views more  IJAR 2011»
13 years 1 months ago
A sequential pattern mining algorithm using rough set theory
Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns in time se...
Ken Kaneiwa, Yasuo Kudo
CLUSTER
2002
IEEE
13 years 9 months ago
Online Prediction of the Running Time of Tasks
Abstract. We describe and evaluate the Running Time Advisor (RTA), a system that can predict the running time of a compute-bound task on a typical shared, unreserved commodity host...
Peter A. Dinda
AAAI
2007
14 years 22 hour ago
The Impact of Time on the Accuracy of Sentiment Classifiers Created from a Web Log Corpus
We investigate the impact of time on the predictability of sentiment classification research for models created from web logs. We show that sentiment classifiers are time dependen...
Kathleen T. Durant, Michael D. Smith