NSPG-Miner: Mining Repetitive Negative Sequential Patterns

TL;DR

NSPG-Miner is an efficient algorithm that simultaneously mines positive and negative sequential patterns with gap constraints, improving pattern discovery in sequential data analysis.

Contribution

The paper introduces NSPG-Miner, a novel algorithm that effectively mines both positive and negative sequential patterns with gap constraints, enhancing pattern discovery capabilities.

Findings

NSPG-Miner outperforms 11 existing algorithms in efficiency.

It discovers more valuable patterns than state-of-the-art methods.

Experimental results validate the effectiveness of the proposed strategies.

Abstract

Sequential pattern mining (SPM) with gap constraints (or repetitive SPM or tandem repeat discovery in bioinformatics) can find frequent repetitive subsequences satisfying gap constraints, which are called positive sequential patterns with gap constraints (PSPGs). However, classical SPM with gap constraints cannot find the frequent missing items in the PSPGs. To tackle this issue, this paper explores negative sequential patterns with gap constraints (NSPGs). We propose an efficient NSPG-Miner algorithm that can mine both frequent PSPGs and NSPGs simultaneously. To effectively reduce candidate patterns, we propose a pattern join strategy with negative patterns which can generate both positive and negative candidate patterns at the same time. To calculate the support (frequency of occurrence) of a pattern in each sequence, we explore a NegPair algorithm that employs a key-value pair array structure to deal with the gap constraints and the negative items simultaneously and can avoid redundant rescanning of the original sequence, thus improving the efficiency of the algorithm. To report the performance of NSPG-Miner, 11 competitive algorithms and 11 datasets are employed. The experimental results not only validate the effectiveness of the strategies adopted by NSPG-Miner, but also verify that NSPG-Miner can discover more valuable information than the state-of-the-art algorithms. Algorithms and datasets can be downloaded from https://github.com/wuc567/Pattern-Mining/tree/master/NSPG-Miner.