Abstract
Many of recent computer applications generate data as a form of data streams, so a study on mining data streams can give valuable results being widely used in the applications. In this paper, a novel weighting technique for mining interesting sequential patterns over a sequence data stream is proposed. Assuming that a sequence with small time-intervals between its data elements is more valuable than others with large time-intervals, the novel interesting sequential pattern is defined and found by analyzing the time-intervals of data elements in a sequence as well as their orders.
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Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2012R1A1B4000651)
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Chang, J.H., Park, NH. (2013). A Novel Weighting Technique for Mining Sequence Data Streams. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_112
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DOI: https://doi.org/10.1007/978-94-007-5860-5_112
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