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- W2333997379 abstract "Given an incomplete (i.e., partially-observed) network, which nodes should we actively probe in order to achieve the highest accuracy for a given network feature? For example, consider a cyber-network administrator who observes only a portion of the network at time t and wants to accurately identify the most important (e.g., highest PageRank) nodes in the complete network. She has a limited budget for probing the network. Of all the nodes she has observed, which should she probe in order to most accurately identify the important nodes? We propose a novel and scalable algorithm, MaxOutProbe, and evaluate it w.r.t. four network features (largest connected component, PageRank, core-periphery, and community detection), five network sampling strategies, and seven network datasets from different domains. Across a range of conditions, MaxOutProbe demonstrates consistently high performance relative to several baseline strategies" @default.
- W2333997379 created "2016-06-24" @default.
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- W2333997379 date "2015-09-30" @default.
- W2333997379 modified "2023-09-27" @default.
- W2333997379 title "Rutgers University Subcontract B611610 Final Report" @default.
- W2333997379 doi "https://doi.org/10.2172/1226949" @default.
- W2333997379 hasPublicationYear "2015" @default.
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