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Titlebook: Advances in Knowledge Discovery and Data Mining, Part I; 14th Pacific-Asia Co Mohammed J. Zaki,Jeffrey Xu Yu,Vikram Pudi Conference proceed

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楼主: 喝水
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https://doi.org/10.1007/978-1-4939-2428-8 expander graphs. We empirically evaluate this method in addition to other online sampling strategies on several real-world social networks. We find that, by sampling nodes to maximize the expansion of the sample, we are able to approximate the set of most influential individuals across . measures of centrality.
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https://doi.org/10.1007/978-3-642-96158-8tly obtained some interesting results: (a) Discovering influential nodes in social networks using the Shapley value, and (b) Identifying topologies of strategically formed social networks using a game theoretic approach.
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Clinical Epidemiology and Biostatisticse tested our technique on major UCI machine learning databases and compared the results to state of the art techniques. Our method resulted in significant improvements in the performance of the K-NN classifier and also performed better than other techniques on major databases.
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