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SLAM: Efficient Sweep Line Algorithms for Kernel Density Visualization

Summary: SLAM: efficient Sweep Line Algorithms for Kernel Density Visualization on million-scale data and high-res grids. RAO yields lowest time complexity; 1–2 order speedups on up to 4.33M points with fast zoom/pan versus state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6340
Venue
SIGMOD
Year
2022
Pagerank
5.093636e-05
Overall Rank
11,533 | 20.88%
DOI
10.1145/3514221.3517823

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BibTeX Citation

@inproceedings{chan_sigmod22,
        title = {{SLAM: Efficient Sweep Line Algorithms for Kernel Density Visualization}},
        author = {Chan, Tsz Nam and U, Leong Hou and Choi, Byron and Xu, Jianliang},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517823},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517823},
        year = {2022}
}

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