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An Optimization Method for Performance Improvement of Set-based Similar Sequence Matching
http://doi.org/10.5626/JOK.2018.45.4.403
The set-based similar sequence matching method involves searching for data set sequences that are similar to a query set sequence. In the method, the similarity between two sets is represented as the size of intersection between them. However, there is a critical performances issue for calculating intersection size if the number of sets is large. In the past, authors of the present work proposed a method to improve the performance of set-based similar sequence matching using simple index structure. In this paper, we propose an optimization method for more efficient running of set-based similar sequence matching. Our method is based on pruning that excludes unnecessary calculation. Through experiments, we show that the proposed method reduces the execution time by about 20% compared to the existing methods.
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