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SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine

Summary: Progressive, content-based SPIRE for multimodal unstructured data; supports image, image sequence, time series, and parametric data in large archives. Dynamic-programming–guided scheduling with hierarchical decorrelation enables progressive refinement on small data portions, yielding 20x+ speedups for template matching/classification and 400–800% for texture extraction, validated on solar flares and petroleum exploration. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3310
Venue
SIGMOD
Year
2000
Pagerank
-
Overall Rank
14,095 | 3.30%
DOI
10.1145/342009.336583

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Authors

BibTeX Citation

@inproceedings{li_sigmod00,
        title = {{SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine}},
        author = {Li, Chung-Sheng and Bergman, Lawrence D. and Chang, Yuan-Chi and Castelli, Vittorio and Smith, John R.},
        series = {{SIGMOD} '00},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/342009.336583},
        url = {https://dl.acm.org/doi/10.1145/342009.336583},
        year = {2000}
}

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7,352 Boolean + Ranking: Querying a Database by K-Constrained Optimization 2006 SIGMOD 5.6353412e-05
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