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CIVET: Exploring Compact Index for Variable-Length Subsequence Matching on Time Series
Summary: CIVET introduces UPAA, a uniform PAA representation that aligns features across variable-length subsequences while preserving lower-bounding. Builds a compact index by grouping adjacent/similar subsequences and uses pruning+filtering to enable exact (no false dismissals), scalable, faster variable-length matching.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13445
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 4.1945683e-05
- Overall Rank
- 11,022 | 23.33%
- DOI
-
10.14778/3665844.3665845
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 65 |
Fast Subsequence Matching in Time-Series Databases |
1994 |
SIGMOD |
0.00062029383 |
| 539 |
Fast Time Sequence Indexing for Arbitrary L_p Norms |
2000 |
VLDB |
0.00020666392 |
| 1,061 |
Warping Indexes with Envelope Transforms for Query by Humming |
2003 |
SIGMOD |
0.00014368716 |
| 1,157 |
A Data-adaptive and Dynamic Segmentation Index for Whole Matching on Time Series |
2013 |
VLDB |
0.00013610658 |
| 1,161 |
Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures |
2008 |
VLDB |
0.00013585236 |
| 3,029 |
A Decade of Progress in Indexing and Mining Large Time Series Databases |
2006 |
VLDB |
7.6803666e-05 |
| 3,540 |
Scalable, Variable-Length Similarity Search in Data Series: The ULISSE Approach |
2018 |
VLDB |
6.9943185e-05 |
| 3,726 |
Indexing Large Human-Motion Databases |
2004 |
VLDB |
6.8148202e-05 |
| 4,219 |
Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series |
2018 |
SIGMOD |
6.3500768e-05 |
| 4,853 |
Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures |
2020 |
SIGMOD |
5.8760276e-05 |
| 5,158 |
Coconut: A Scalable Bottom-Up Approach for Building Data Series Indexes |
2018 |
VLDB |
5.6588553e-05 |
| 5,770 |
ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines |
2020 |
SIGMOD |
5.3328309e-05 |
| 7,095 |
Dumpy: A Compact and Adaptive Index for Large Data Series Collections |
2023 |
SIGMOD |
4.8350023e-05 |
| 8,778 |
The Inherent Time Complexity and An Efficient Algorithm for Subsequence Matching Problem |
2022 |
VLDB |
4.4543399e-05 |
| 9,425 |
Hum-a-song: A Subsequence Matching with Gaps-Range-Tolerances Query-By-Humming System |
2012 |
VLDB |
4.3441378e-05 |
| 9,428 |
A Subsequence Matching with Gaps-Range-Tolerances Framework: A Query-By-Humming Application |
2011 |
VLDB |
4.3441378e-05 |
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| Overall Rank |
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2022 |
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4.4543399e-05 |
| 65 |
Fast Subsequence Matching in Time-Series Databases |
1994 |
SIGMOD |
0.00062029383 |