计算机科学
杠杆(统计)
同种类的
数据科学
异构网络
集合(抽象数据类型)
数据挖掘
人工智能
电信
热力学
无线网络
物理
程序设计语言
无线
出处
期刊:SIGKDD explorations
[Association for Computing Machinery]
日期:2013-04-30
卷期号:14 (2): 20-28
被引量:473
标识
DOI:10.1145/2481244.2481248
摘要
Most objects and data in the real world are of multiple types, interconnected, forming complex, heterogeneous but often semi-structured information networks. However, most network science researchers are focused on homogeneous networks, without distinguishing different types of objects and links in the networks. We view interconnected, multityped data, including the typical relational database data, as heterogeneous information networks, study how to leverage the rich semantic meaning of structural types of objects and links in the networks, and develop a structural analysis approach on mining semi-structured, multi-typed heterogeneous information networks. In this article, we summarize a set of methodologies that can effectively and efficiently mine useful knowledge from such information networks, and point out some promising research directions.
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