Aggregated deletion propagation for counting conjunctive query answers∗
We investigate the computational complexity of minimizing the source side-effect in order to remove a given number of tuples from the output of a conjunctive query. This is a variant of the well-studied deletion propagation problem, the difference being that we are interested in removing the smallest subset of input tuples to remove a given number of output tuples while deletion propagation focuses on removing a specific output tuple. We call this the Aggregated Deletion Propagation problem. We completely characterize the poly-time solvability of this problem for arbitrary conjunctive queries without self-joins. This includes a poly-time algorithm to decide solvability, as well as an exact structural characterization of NP-hard instances. We also provide a practical algorithm for this problem (a heuristic for NP-hard instances) and evaluate its experimental performance on real and synthetic datasets.
Duke Scholars
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Related Subject Headings
- 4605 Data management and data science
- 0807 Library and Information Studies
- 0806 Information Systems
- 0802 Computation Theory and Mathematics
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- 4605 Data management and data science
- 0807 Library and Information Studies
- 0806 Information Systems
- 0802 Computation Theory and Mathematics