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سند علمی

Google matrix analysis of directed networks

Leonardo Ermann, Klaus M. Frahm, Dima Shepelyansky

چکیده

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Due to the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines use extensively such methods. It is highly important to develop new tools to classify and rank massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos and Random Matrix theory.

اسناد مشابه

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