Continuous Multiplicative Attribute Graph Model

doi:10.1007/s12204-017-1805-9

Abstract

Abstract: Network modeling is an important approach in many fields in analyzing complex systems. Recently new series of methods have emerged, by using Kronecker product and similar tools to model real systems. One of such approaches is the multiplicative attribute graph (MAG) model, which generates networks based on category attributes of nodes. In this paper we try to extend this model into a continuous one, give an overview of its properties, and discuss some special cases related to real-world networks, as well as the influence of attribute distribution and affinity function respectively.

Key words: multiplicative attribute graph model| social network| continuous attribute

摘要： Network modeling is an important approach in many fields in analyzing complex systems. Recently new series of methods have emerged, by using Kronecker product and similar tools to model real systems. One of such approaches is the multiplicative attribute graph (MAG) model, which generates networks based on category attributes of nodes. In this paper we try to extend this model into a continuous one, give an overview of its properties, and discuss some special cases related to real-world networks, as well as the influence of attribute distribution and affinity function respectively.

关键词: multiplicative attribute graph model| social network| continuous attribute

CLC Number:

TP 181

HUANG Jiaxuan (黄嘉烜), JIN Xiaogang* (金小刚). Continuous Multiplicative Attribute Graph Model[J]. Journal of shanghai Jiaotong University (Science), 2017, 22(1): 87-091.

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