Memory-Efficient Sequential Pattern Mining with Hybrid Tries

arXiv:2202.06834v2 Announce Type: replace-cross
Abstract: As modern data sets continue to grow exponentially in size, the demand for efficient mining algorithms capable of handling such large data sets becomes increasingly imperative. This paper develops a memory-efficient approach for Sequential Pattern Mining (SPM), a fundamental topic in knowledge discovery that faces a well-known memory bottleneck for large data sets. Our methodology involves a novel hybrid trie data structure that exploits recurring patterns to compactly store the data set in memory; and …

abstract algorithms arxiv cs.ai cs.db cs.ds cs.lg data data sets demand discovery hybrid knowledge memory mining modern paper spm type