论文标题
对位置驱动影响最大化的调查
A Survey on Location-Driven Influence Maximization
论文作者
论文摘要
旨在从社交网络中选择一组用户以最大化预期受影响的用户数量的影响最大化（IM）是一个常绿的热门研究主题。它的研究结果极大地影响了现实世界的应用程序，例如业务营销。过去十年的基于位置的基于位置的网络平台吸引了研究人员将位置信息嵌入传统IM研究中。在这项调查中，我们从以下关键方面的角度对现有的位置驱动IM研究进行了全面综述：（1）对这些作品的应用程序场景进行综述，（2）评估影响影响传播的扩散模型，以及（3）对处理位置驱动的IM问题以及针对加速技术的特定问题的方法的全面研究。最后，我们将前景带入未来IM研究的研究方向。
Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its research outcomes significantly impact real-world applications such as business marketing. The booming location-based network platforms of the last decade appeal to the researchers embedding the location information into traditional IM research. In this survey, we provide a comprehensive review of the existing location-driven IM studies from the perspective of the following key aspects: (1) a review of the application scenarios of these works, (2) the diffusion models to evaluate the influence propagation, and (3) a comprehensive study of the approaches to deal with the location-driven IM problems together with a particular focus on the accelerating techniques. In the end, we draw prospects into the research directions in future IM research.
