Data mining: concepts and techniques
Data mining: concepts and techniques
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Using Sequential and Non-Sequential Patterns in Predictive Web Usage Mining Tasks
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Sequential Patterns from Multidimensional Sequence Data
IEEE Transactions on Knowledge and Data Engineering
A method for detecting arrhythmia using a RR interval from ECG data in U-Health system
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
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In USN systems, data streams are generated from sensor nodes. It is very important to find information from these data stream because data streams present practical phenomena. Data streams have temporal properties, so we can apply sequential pattern mining methods to data streams. However, because data streams are continuous and infinite, we need to develop new methods by considering the conditions in USN environments. In this paper, we propose a real-time sequential pattern mining methods for data stream from USN systems. We define the variable Meaning Window and use HAPT (HAsh based Pattern Tree) as a new data structures for sequential pattern mining. To evaluate the performance of our proposed methods, we compared it with the PrefixSpan method. Through experimentation, we confirmed the effectiveness our methods for USN system environments.