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• W3003647546 abstract "Abstract Spreading dynamics analysis is an important and interesting topic since it has many applications such as rumor or disease controlling, viral marketing and information recommending. Many state-of-the-art researches focus on predicting infection scale or threshold. Few researchers pay attention to the predicting of infection nodes from a snapshot. With developing of precision marketing, recommending and, controlling, how to predict infection nodes precisely from snapshot becomes a key issue in spreading dynamics analysis. In this paper, a probability based prediction model is presented so as to estimate the infection nodes from a snapshot of spreading. Experimental results on synthetic and real networks demonstrate that the model proposed could predict the infection nodes precisely in the sense of probability." @default.
• W3003647546 created "2020-02-07" @default.
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• W3003647546 date "2020-01-28" @default.
• W3003647546 modified "2023-10-15" @default.
• W3003647546 title "Spreading predictability in complex networks" @default.
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• W3003647546 doi "https://doi.org/10.1101/2020.01.28.922757" @default.
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