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DAWAK
2008
Springer

Mining Serial Episode Rules with Time Lags over Multiple Data Streams

8 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 study a special episode rule, named serial episode rule with a time lag in an environment of multiple data streams. This rule can be widely used in different applications, such as traffic monitoring over multiple car passing streams in highways. Mining serial episode rules over the data stream environment is a challenge due to the high data arrival rates and the infinite length of the data streams. In this paper, we propose two methods considering different criteria on space utilization and precision to solve the problem by using a prefix tree to summarize the data streams and then traversing the prefix tree to generate the rules. A series of experiments on real data is performed to evaluate the two methods. Keyword: Multiple data streams, Data mining, Serial episode rule, Time lag.
Tung-Ying Lee, En Tzu Wang, Arbee L. P. Chen
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where DAWAK
Authors Tung-Ying Lee, En Tzu Wang, Arbee L. P. Chen
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