Mining Heterogeneous Information Networks: A Review

Rohit Chivukula, T. Lakshmi
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Abstract

An information network is modelled as a graph with vertices denoting entities and links depicting connections within them. Heterogeneous Information Network (HIN) contains multiple types of vertices and multiple types of links. There is vast amount of hidden knowledge available in the HINs. Most of the techniques proposed in the literature are focused on homogeneous networks. The same methods are applied for heterogeneous networks by considering homogeneous projections. But this approach leads to information loss. In this paper, major mining tasks applicable for Heterogeneous Information Networks are reviewed.
异构信息网络挖掘:综述
信息网络被建模为一个图形,其中顶点表示实体,链接表示实体内部的连接。异构信息网络(HIN)包含多种类型的顶点和多种类型的链路。HINs中有大量隐藏的知识。文献中提出的大多数技术都集中在同构网络上。通过考虑同质投影,对异质网络应用了相同的方法。但是这种方法会导致信息丢失。本文综述了适用于异构信息网络的主要挖掘任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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