Efficient and accurate query evaluation on uncertain graphs via recursive stratified sampling

@article{Li2014EfficientAA,
  title={Efficient and accurate query evaluation on uncertain graphs via recursive stratified sampling},
  author={Rong-Hua Li and Jeffrey Xu Yu and Rui Mao and Tan Jin},
  journal={2014 IEEE 30th International Conference on Data Engineering},
  year={2014},
  pages={892-903}
}
In this paper, we introduce two types of query evaluation problems on uncertain graphs: expectation query evaluation and threshold query evaluation. Since these two problems are #P-complete, most previous solutions for these problems are based on naive Monte-Carlo (NMC) sampling. However, NMC typically leads to a large variance, which significantly reduces its effectiveness. To overcome this problem, we propose two classes of estimators, called class-I and class-II estimators, based on the idea… CONTINUE READING

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Efficient and accurate query evaluation on uncertain graphs via recursive stratified sampling

  • R.-H. Li, J. X. Yu, R. Mao, T. Jin
  • Technical Report, Available at http://nhpcc.szu…
  • 2013
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