A Novel Weighting Technique for Mining Sequence Data Streams

  • Joong Hyuk Chang
  • Nam-Hun Park
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)


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.


Weighted sequential pattern Time-interval weight Sequence data streams Data stream mining 



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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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Computer and Information TechnologyDaegu UniversityGyeongbukRepublic of Korea
  2. 2.Department of Computer ScienceAnyang UniversityIncheonRepublic of Korea

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