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ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines

Summary: ShapeSearch enables flexible, approximate pattern search over trendlines via sketch, natural language, or visual-regular-expression inputs. A minimal shape querying algebra with a fast, query-aware engine and perceptual scoring enables interactive, scalable trendline exploration on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5999
Venue
SIGMOD
Year
2020
Pagerank
6.2134177e-05
Overall Rank
5,454 | 62.59%
DOI
10.1145/3318464.3389722

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{siddiqui_sigmod20,
        title = {{ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines}},
        author = {Siddiqui, Tarique and Luh, Paul and Wang, Zesheng and Karahalios, Karrie and Parameswaran, Aditya G.},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389722},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389722},
        year = {2020}
}

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