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Discovering Longest-lasting Correlation in Sequence Databases

Summary: Discovering the longest-lasting highly correlated subsequences in sequence databases without a predefined query length. Introduces a space-constrained index with intra- and inter-object grouping that bounds correlations for subsequences of similar length and offset, enabling a normalized distance metric and scalable evaluation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10654
Venue
VLDB
Year
2013
Pagerank
4.9669225e-05
Overall Rank
6,671 | 53.60%
DOI
-

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