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[2H5-OS-8a-04] Proposal for Localised Sequential Pattern Mining based on Swarm Intelligence
Keywords:data mining, swarm intelligence
The recent spread of IoT technology has accumulated a so large amount of information, that we cannot process them enough. Data mining methods are required to extract useful information from such information.
The objective of this study is to construct an algorithm that can efficiently extract highly frequent or highly localised patterns from a single sequential data. Specifically, we propose a method for extracting these patterns based on the swarm intelligence mechanism.
We applied the proposed method to pseudo-created series data, and confirmed that the proposed method extracted patterns depending on their frequency and localisation.
The objective of this study is to construct an algorithm that can efficiently extract highly frequent or highly localised patterns from a single sequential data. Specifically, we propose a method for extracting these patterns based on the swarm intelligence mechanism.
We applied the proposed method to pseudo-created series data, and confirmed that the proposed method extracted patterns depending on their frequency and localisation.
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