An Efficient Approach for Mining Top-K Fault-Tolerant Repeating Patterns
In this paper, an efficient strategy for mining top-K non-trivial fault-tolerant repeating patterns (FT-RPs in short) with lengths no less than min_len from data sequences is provided. By extending the idea of appearing bit sequences, fault-tolerant appearing bit sequences are defined to represent the locations where candidate patterns appear in a data sequence with insertion/deletion errors being allowed. Two algorithms, named TFTRP-Mine(Top-K non-trivial FT-RPs Mining) and RE-TFTRP-Mine (REfinement of TFTRP-Mine), respectively, are proposed. Both of these two algorithms use the recursive formulas to obtain the fault-tolerant appearing bit sequence of a pattern systematically and then the fault-tolerant frequency of each candidate pattern could be counted quickly. Besides, RE-TFTRP-Mine adopts two additional strategies for pruning the searching space in order to improve the mining efficiency. The experimental results show that RE-TFTRP-Mine outperforms TFTRP-Mine algorithm when K and min_len are small. In addition, more important and implicit repeating patterns could be found from real music objects by adopting fault tolerant mining.
KeywordsExecution Time Data Item Fault Tolerance Recursive Formula Recursive Function
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