[KDD 2020] Z-Miner: an efficient method for mining frequent arrangements of event intervals - CrossMinds.ai
[KDD 2020] Z-Miner: an efficient method for mining frequent arrangements of event intervals
Aug 13, 20203 views
Zed Lee
Mining frequent patterns of event intervals from a large collection,of interval sequences is a problem that appears in several application domains. In this paper, we propose,Z-Miner,, a novel algorithm,for solving this problem that addresses the deficiencies of existing,competitors by employing two novel data structures:,Z-Table,, a,hierarchical hash-based data structure for time-efficient candidate,generation and support count, and,Z-Arrangement,, a data structure for efficient memory consumption. The proposed algorithm,is able to handle patterns with repetitions of the same event label, allowing for gap and error tolerance constraints, as well as,keeping track of the exact occurrences of the extracted frequent,patterns. Our experimental evaluation on eight real-world and six,synthetic datasets demonstrates the superiority of,Z-Miner,against,four state-of-the-art competitors in terms of runtime efficiency and,memory footprint.
SIGKDD_2020
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