网络环境下的信息源查找：预算查询
Information Source Finding in Networks: Querying with Budgets
摘要：
在本文中，我们研究了一个问题，通过查询个人的扩散信息的来源，给定一个样本快照的信息扩散图，其中两个查询被问：{ \em（i）}是否响应源或没有，和{ \em（ii）}如果没有，哪个邻居传播的信息的响应。我们考虑的情况下，受访者可能并不总是真实的，一些成本是采取每个查询。我们的目标是量化的必要和足够的预算，以实现检测概率$1-δ$为任何给定的$0<δ<1.$为此，我们研究了两种类型的算法：自适应和非自适应的，其中每一个对应于我们是否自适应地选择下一个受访者的答案的基础上，以前的受访者或没有。首先，我们提供了信息理论的必要的预算在这两种算法类型的下限。在足够的预算方面，我们提出了两个实用的估计算法，每一个非自适应和自适应类型，并为每一种算法，我们定量分析的预算，以确保$1-δ$检测精度。该理论分析不仅量化了实际估计算法在找到扩散源时实现给定目标检测精度所需的预算，而且还使我们能够定量地表征非自适应类型估计所需的额外预算的量，称为{ \em自适应间隙}。我们验证了我们的理论研究结果在合成和现实世界的社交网络拓扑结构。
英文摘要：
In this paper, we study a problem of detecting the source of diffused information by querying individuals, given a sample snapshot of the information diffusion graph, where two queries are asked: {\em (i)} whether the respondent is the source or not, and {\em (ii)} if not, which neighbor spreads the information to the respondent. We consider the case when respondents may not always be truthful and some cost is taken for each query. Our goal is to quantify the necessary and sufficient budgets to achieve the detection probability $1-δ$ for any given $0<δ<1.$ To this end, we study two types of algorithms: adaptive and non-adaptive ones, each of which corresponds to whether we adaptively select the next respondents based on the answers of the previous respondents or not. We first provide the information theoretic lower bounds for the necessary budgets in both algorithm types. In terms of the sufficient budgets, we propose two practical estimation algorithms, each of non-adaptive and adaptive types, and for each algorithm, we quantitatively analyze the budget which ensures $1-δ$ detection accuracy. This theoretical analysis not only quantifies the budgets needed by practical estimation algorithms achieving a given target detection accuracy in finding the diffusion source, but also enables us to quantitatively characterize the amount of extra budget required in non-adaptive type of estimation, refereed to as {\em adaptivity gap}. We validate our theoretical findings over synthetic and real-world social network topologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
