Abstract
A fundamental research problem concerning edge-labeled uncertain graphs is called label and distance-constraint reachability query (LDCR): Given two vertices u and v, query the probability that u can reach v through paths whose labels and lengths are constrained by a label set and a distance threshold separately. Considering LDCR is not tractable as a #P-complete problem, we aim to propose effective and efficient approximate solutions for it. We first introduce a subpath-based filtering strategy which combines divide-conquer algorithm and branch path pruning to compress the original graph and reduce the scale of DC-tree. Then to approximate LDCR, several estimators are presented based on different sampling mechanisms and a path/cut bound is proposed to prune large-deviation values. An extensive experimental evaluation on both real and synthetic datasets demonstrates that our approaches exhibit prominent performance in term of query time and accuracy.
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Chen, M., Gu, Y., Bao, Y., Yu, G. (2014). Label and Distance-Constraint Reachability Queries in Uncertain Graphs. In: Bhowmick, S.S., Dyreson, C.E., Jensen, C.S., Lee, M.L., Muliantara, A., Thalheim, B. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science, vol 8421. Springer, Cham. https://doi.org/10.1007/978-3-319-05810-8_13
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DOI: https://doi.org/10.1007/978-3-319-05810-8_13
Publisher Name: Springer, Cham
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