CRAWD: Sampling-Based Estimation of Count-Distinct SPARQL Queries - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

CRAWD: Sampling-Based Estimation of Count-Distinct SPARQL Queries

Résumé

Count-distinct SPARQL queries compute the number of unique values in the results of a query executed on a Knowledge Graph. However, counting the exact number of distinct values is often computationally demanding and time-consuming. As a result, these queries often fail on public SPARQL endpoints due to fair use policies. In this paper, we propose CRAWD, a new sampling-based approach designed to approximate count-distinct SPARQL queries. CRAWD significantly improves sampling efficiency and allows feasible execution of count-distinct SPARQL queries on public SPARQL endpoints, considerably improving existing methods.
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Dates et versions

hal-04726343 , version 1 (08-10-2024)

Identifiants

  • HAL Id : hal-04726343 , version 1

Citer

Thi Hoang Thi Pham, Pascal Molli, Brice Nédelec, Hala Skaf-Molli, Julien Aimonier-Davat. CRAWD: Sampling-Based Estimation of Count-Distinct SPARQL Queries. International Semantic Web Conference, Nov 2024, Maryland, United States. ⟨hal-04726343⟩
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