2012/10/17 by Jianguo Wang, Wang, Jack
Computer Science · #Advanced Database Systems and Queries #Computational Geometry (cs.CG) #Data Management and Algorithms #Data Structures and Algorithms (cs.DS) #Databases (cs.DB) #FOS: Computer and information sciences #G.3 #H.2.8 #H.3.3 #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.1210.4663
openalex publication_date 2012/10/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This article proposes an PQR search method for probabilistic objects. The main idea of our method is to use a strategy called pre-approximation that can reduce the initial problem to a highly simplified version, implying that it makes the rest of steps easy to tackle. In particular, this strategy itself is pretty simple and easy to implement. Furthermore, motivated by the cost analysis, we further optimize our solution. The optimizations are mainly based on two insights: (\romannumeral 1) the number of effective subdivisions is no more than 1; and (\romannumeral 2) an entity with the larger span is more likely to subdivide a single region. We demonstrate the effectiveness and efficiency of our proposed approaches through extensive experiments under various experimental settings.