用昂贵的网络信息播种

Dean Eckles, Hossein Esfandiari, Elchanan Mossel, M. Amin Rahimian
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引用次数: 12

摘要

在联系结构的基础上播种最具影响力的个人可以大大提高在社会网络中的传播程度。大多数影响最大化的文献假设了整个网络图的知识。然而,在实践中,获得网络结构的全部知识是非常昂贵的。我们提出了多项式时间算法,该算法使用对图结构的有限数量的查询来提供几乎严格的近似保证。我们还提供了不可能结果,以降低查询复杂度,并显示我们保证的严密性。
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Seeding with Costly Network Information
Seeding the most influential individuals based on the contact structure can substantially enhance the extent of a spread over the social network. Most of the influence maximization literature assumes the knowledge of the entire network graph. However, in practice, obtaining full knowledge of the network structure is very costly. We propose polynomial-time algorithms that provide almost tight approximation guarantees using a bounded number of queries to the graph structure. We also provide impossibility results to lower bound the query complexity and show tightness of our guarantees.
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