A Survey of Heterogeneous Information Network Analysis
A Survey of Heterogeneous Information Network Analysis
复制标题
异构信息网络分析综述
DOI：
10.1109/tkde.2016.2598561
复制
发表时间：
2017-01-01
影响因子：
8.9
通讯作者：
Yu, Philip S.
中科院分区：
文献类型：
--
作者：
Shi, Chuan;Li, Yitong;Yu, Philip S.
大多数真实的系统由大量相互作用的多类型组件组成，而大多数当代研究将它们建模为同构信息网络，而不区分网络中不同类型的对象和链接。近年来，越来越多的研究者开始将这些相互关联的、多类型的数据视为异构信息网络，并利用网络中对象和链接的结构类型的丰富语义来开发结构化分析方法。与广泛研究的同构信息网络相比，异构信息网络包含了更丰富的结构和语义信息，这为数据挖掘提供了机遇，也带来了挑战。在本文中，我们提供了一个调查异构信息网络分析。我们将介绍异构信息网络分析的基本概念，研究它在不同的数据挖掘任务的发展，讨论一些先进的主题，并指出一些未来的研究方向。
Most real systems consist of a large number of interacting, multi-typed components, while most contemporary researches model them as homogeneous information networks, without distinguishing different types of objects and links in the networks. Recently, more and more researchers begin to consider these interconnected, multi-typed data as heterogeneous information networks, and develop structural analysis approaches by leveraging the rich semantic meaning of structural types of objects and links in the networks. Compared to widely studied homogeneous information network, the heterogeneous information network contains richer structure and semantic information, which provides plenty of opportunities as well as a lot of challenges for data mining. In this paper, we provide a survey of heterogeneous information network analysis. We will introduce basic concepts of heterogeneous information network analysis, examine its developments on different data mining tasks, discuss some advanced topics, and point out some future research directions.