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2018 IEEE 34th International Conference on Data Engineering (ICDE) (2018)
Paris, France
Apr 16, 2018 to Apr 19, 2018
ISSN: 2375-026X
ISBN: 978-1-5386-5520-7
pp: 1755-1756
In this paper, we consider probabilistic reachability queries on uncertain graphs. To make the results more informative, we adopt a crowdsourcing-based approach to clean the uncertain edges. One important problem is how to efficiently select a limited set of edges for cleaning that maximizes the quality improvement. We prove that the edge selection problem is #P-hard. In light of the hardness of the problem, we propose a series of edge selection algorithms, followed by a number of optimization techniques and pruning heuristics for minimizing the computation time. Our experimental results demonstrate that our proposed techniques outperform a random selection by up to 27 times in terms of the result quality improvement and the brute-force solution by up to 60 times in terms of the elapsed time.
computational complexity, data handling, graph theory, optimisation, probability, query processing, reachability analysis

X. Lin, Y. Peng, J. Xu and B. Choi, "Human-Powered Data Cleaning for Probabilistic Reachability Queries on Uncertain Graphs," 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 2018, pp. 1755-1756.
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