The Solution to Node Importance in Complex Networks Based on PageRank Algorithm

Guang Li Li; Han Li; Ye Ran Wang; Tong Bo Zhang

doi:10.4028/www.scientific.net/AMM.599-601.1777

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 599-601The Solution to Node Importance in Complex...

The Solution to Node Importance in Complex Networks Based on PageRank Algorithm

Abstract:

Network science is an emerging interdiscipline that can solve practical issues by researching and analyzing properties of complex networks. In this paper, a modified algorithm based on PageRank is developed to construct the evaluation model in directed-weighted networks. This model can effectively determine the node importance in networks. Discussions about how to construct networks with the use of relationship between data and how to determine the weight of edges form the major concern of the present studies. Schemes for solving the above issues can differ in different networks. We successfully apply this model to citation, co-author and weibo follower networks. Through the results, we find that this optimized model can efficiently evaluate the importance of nodes in different complex networks and has strong applicability.

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Periodical:

Applied Mechanics and Materials (Volumes 599-601)

Pages:

1777-1780

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.599-601.1777

Citation:

Cite this paper

Online since:

August 2014

Authors:

Guang Li Li*, Han Li, Ye Ran Wang, Tong Bo Zhang

Keywords:

Complex Network, Influence Evaluation, PageRank Algorithm

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* - Corresponding Author

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