动态信息网关键技术的研究进展  

Research progress of key technologies in dynamic information networks

作　　者：王芯蕊 高宏[1] WANG Xinrui;GAO Hong(School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China)

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001

出　　处：《智能计算机与应用》2022年第10期234-238,F0003,共6页Intelligent Computer and Applications

基　　金：国家自然科学基金(U19A2059)。

摘　　要：信息网,表示了真实世界中众多的对象和对象之间的联系,在多种现实应用中广泛存在。对信息网的分析研究具有重要的实际意义和广阔的应用前景。在实际中,信息网上的对象和联系常常随着时间的推移不断发生变化,这样的信息网被称为动态信息网。近年来,动态信息网受到了很多的关注。目前对于动态信息网关键技术的研究主要集中在社区探测和社区搜索、离群点探测、影响力最大化、链接预测。本文详细介绍了这些关键技术的概念、发展和在动态信息网上的研究进展,之后讨论了动态信息网关键技术研究仍然面临的挑战,以及未来可能的研究方向。Information networks, which represent a large number of objects and the links among them in the real world, are omnipresent in various kinds of practical applications. The analysis and research of information networks has great practical significance and broad application prospect. In reality, information networks are usually dynamic where objects and links among them change drastically over time. Such information networks are called dynamic information networks. In recent years, dynamic information networks have attracted much attention. At present, the research on the key technologies in dynamic information networks mainly focuses on community detection and community search, outlier detection, influence maximization and link prediction. This paper introduces the concepts and development of those key technologies, as well as their research progress in dynamic information networks. Based on the above, the paper discusses several challenges and future research directions for the research on key technologies in dynamic information networks.

关 键 词：动态信息网 社区探测和社区搜索 离群点探测 影响力最大化 链接预测 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]