Relevance Queries for Interval Data
Summary: Defines overlap-based relevance scores for interval data and relevance queries that return the most relevant intersecting intervals. Presents a framework to evaluate these queries on standard interval indices (interval tree, HINT) with real-data experiments showing speedups over baselines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Panagiotis Bouros (Johannes Gutenberg University Mainz)
- 2. Nikos Mamoulis (Athena Research Center; University of Ioannina)
BibTeX Citation
@inproceedings{bouros_sigmod25,
title = {{Relevance Queries for Interval Data}},
author = {Bouros, Panagiotis and Mamoulis, Nikos},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725343},
url = {https://dl.acm.org/doi/10.1145/3725343},
year = {2025}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,244 | FIRAS: A Framework for Interval Range Search and Sampling | 2026 | SIGMOD | 5.093636e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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