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VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series

Summary: VALMOD enables scalable, exact discovery of variable-length motifs in data series, avoiding brute-force across lengths. It yields a length-invariant motif ranking and a meta-data structure to guide length choice, with a visualization-driven demo. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5517
Venue
SIGMOD
Year
2018
Pagerank
9.1660405e-05
Overall Rank
2,260 | 84.28%
DOI
10.1145/3183713.3193556

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
4,219 Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series 2018 SIGMOD 6.3500768e-05
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