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Computing Complex Temporal Join Queries Efficiently

Summary: Multi-way temporal joins on intervals; reduces intermediates via overlap-aware processing. Durable temporal joins; classify joins; linear-time iff r-hierarchical (3SUM); output-sensitive methods for non-r-hierarchical cases; implemented. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6407
Venue
SIGMOD
Year
2022
Pagerank
5.4608734e-05
Overall Rank
8,235 | 43.51%
DOI
10.1145/3514221.3517893

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{hu_sigmod22,
        title = {{Computing Complex Temporal Join Queries Efficiently}},
        author = {Hu, Xiao and Sintos, Stavros and Gao, Junyang and Agarwal, Pankaj K. and Yang, Jun},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517893},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517893},
        year = {2022}
}

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