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| http://dx.doi.org/10.1093/infdis/jiaa234 | DOI Listing |
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Budget-aware local influence iterative algorithm for efficient influence maximization in social networks.
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Département d'Analytique, Opérations et Technologies de l'Information, Université de Québec à Montreal, 315, Sainte-Catherine Street East, H2X 3X2, Montreal, Canada.
The budgeted influence maximization (BIM) problem aims to identify a set of seed nodes that adhere to predefined budget constraints within a specified network structure and cost model. However, it is difficult for the existing algorithms to achieve a balance between timeliness and effectiveness. To address this challenge, our study initially proposes a refined cost model through empirical scrutiny of Weibo's quote data.
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Climate change represents an urgent global threat. Without action, rising temperatures resulting from human activity will increasingly affect our health and wellbeing through changing patterns of disease, extreme weather events and availability of resources. Expedient decarbonisation of the UK economy is an ambitious goal to which we must all contribute.
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