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In this paper, we propose a new representation, Uniform Piecewise Aggregate Approximation (UPAA) with the capability of aligning features for variable-length time series while remaining the lower bounding property. Based on UPAA, we present a compact index structure by grouping adjacent subsequences and similar subsequences respectively. Moreover, we propose an index pruning algorithm and a data filtering strategy to efficiently support variable-length subsequence matching without false dismissals. The experiments conducted on both real and synthetic datasets demonstrate that our approach achieves considerably better efficiency, scalability, and effectiveness than existing approaches.<\/jats:p>","DOI":"10.14778\/3665844.3665845","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T22:19:07Z","timestamp":1722982747000},"page":"2123-2135","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["CIVET: Exploring Compact Index for Variable-Length Subsequence Matching on Time Series"],"prefix":"10.14778","volume":"17","author":[{"given":"Haoran","family":"Xiong","sequence":"first","affiliation":[{"name":"Fudan University"}]},{"given":"Hang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University"}]},{"given":"Zeyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Fudan University"}]},{"given":"Zhenying","family":"He","sequence":"additional","affiliation":[{"name":"Fudan University"}]},{"given":"Peng","family":"Wang","sequence":"additional","affiliation":[{"name":"Fudan University"}]},{"given":"X. 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