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Continuous multiplicative attribute graph model

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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.

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Acknowledgment

We gratefully thank our colleagues Jin Cheng and Li Yi-fu, who have generously discussed with us and helped providing inspiration for our research.

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Authors and Affiliations

  1. Institute of Artifical Intelligence, College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China

    Jiaxuan Huang  (黄嘉烜) & Xiaogang Jin  (金小刚)

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  1. Jiaxuan Huang  (黄嘉烜)
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  2. Xiaogang Jin  (金小刚)
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Corresponding author

Correspondence to Xiaogang Jin  (金小刚).

Additional information

Foundation item: the National Natural Science Foundation of China (No. 61379074) and the Zhejiang Provincial Natural Science Foundation of China (No. LZ12F02003)

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Huang, J., Jin, X. Continuous multiplicative attribute graph model. J. Shanghai Jiaotong Univ. (Sci.) 22, 87–91 (2017). https://doi.org/10.1007/s12204-017-1805-9

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  • DOI: https://doi.org/10.1007/s12204-017-1805-9

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