Bonifati, A. and Dumbrava, S. and Fletcher, G. and Hidders, Jan and Hofer, M. and Martens, W. and Murlak, F. and Shinavier, J. and Staworko, S. and Tomaszuk, D. (2022) Threshold queries in theory and in the wild. In: Özcan, F. and Freire, J. and Lin, X. (eds.) Proceedings of the VLDB Endowment. VLDB Endowment, pp. 1105-1118.
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Abstract
Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. In this paper, we present a deep theoretical analysis of threshold query evaluation and show that thresholds can be used to significantly improve the asymptotic bounds of state-of-the-art query evaluation algorithms. We also empirically show that threshold queries are significant in practice. In surprising contrast to conventional wisdom, we found important scenarios in real-world data sets in which users are interested in computing the results of queries up to a certain threshold, independent of a ranking function that orders the query results.
Metadata
| Item Type: | Book Section |
|---|---|
| Additional Information: | Best Regular Research Paper Runner Up |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Birkbeck Knowledge Lab |
| Depositing User: | Jan Hidders |
| Date Deposited: | 22 May 2024 11:47 |
| Last Modified: | 23 May 2024 05:10 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/53510 |
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