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Evaluating Top-k Queries with Inconsistency Degrees

Summary: Proposes inconsistency-aware top-k evaluation under denial constraints, with two inconsistency measures (single/multi) quantified by why-provenance and provenance polynomials. Presents a top-k algorithm for monotone/non-monotone scoring, with gains over full ranking. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12106
Venue
VLDB
Year
2020
Pagerank
4.5717374e-05
Overall Rank
8,148 | 43.38%
DOI
10.14778/3407790.3407815

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
6,470 Fast Algorithms for Denial Constraint Discovery 2023 VLDB 5.0439835e-05
7,666 Fast Detection of Denial Constraint Violations 2022 VLDB 4.6792751e-05
10,555 Evaluating Continuous Queries with Inconsistency Annotations 2025 VLDB 4.1905499e-05
11,465 INCA: Inconsistency-Aware Data Profiling and Querying 2021 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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