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Top-K Possible Shortest Path Query over a Large Uncertain Graph

  • Lei Zou
  • Peng Peng
  • Dongyan Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6997)

Abstract

This paper studies the top-k possible shortest path (kSP) queries in a large uncertain graph, specifically, given two vertices S and T, a kSP query reports the top-k possible shortest paths from S to T. Different from existing solutions for uncertain graph problems, we adopt the possible worlds semantics. Although possible worlds semantics have been studied widely in relational databases, the graph structure leads to more complexity in computational model. The main contribution of this paper lies in developing lower and upper bounds for the probability that one path is the shortest path in an uncertain graph, based on which, a filter-and-refine framework is proposed to answer kSP queries. We demonstrate the superiority of our method by extensive experiments.

Keywords

Short Path Monte Carlo Common Edge Path Query World Semantic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Lei Zou
    • 1
  • Peng Peng
    • 1
  • Dongyan Zhao
    • 1
  1. 1.Peking UniversityBeijingChina

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