Connecting network science and information theory

Autor(es)

de Arruda, Henrique F. ^[1] ; Silva, Filipi N. ^{[2, 3]} ; Comin, Cesar H. ^[2] ; Amancio, Diego R. ^{[1, 3]} ; Costa, Luciano da F. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos, SP - Brazil

^[3] Indiana Univ, Sch Informat Comp & Engn, Bloomington, IN - USA

• Tipo de documento: Artigo Científico
• Fonte: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 515, p. 641-648, FEB 1 2019.
• Citações Web of Science: 0

Resumo

A framework integrating information theory and network science is proposed. By incorporating and integrating concepts such as complexity, coding, topological projections and network dynamics, the proposed network-based framework paves the way not only to extending traditional information science, but also to modeling, characterizing and analyzing a broad class of real-world problems, from language communication to DNA coding. Basically, an original network is supposed to be transmitted, with or without compaction, through a sequence of symbols or time-series obtained by sampling its topology by some network dynamics, such as random walks. We show that the degree of compression is ultimately related to the ability to predict the frequency of symbols based on the topology of the original network and the adopted dynamics. The potential of the proposed approach is illustrated with respect to the efficiency of transmitting several types of topologies by using a variety of random walks. Several interesting results are obtained, including the behavior of the Barabasi Albert model oscillating between high and low performance depending on the considered dynamics, and the distinct performances obtained for two geographical models. (C) 2018 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 15/18942-8 - Associando redes complexas com espaços efetivos de atributos
• Beneficiário: Cesar Henrique Comin
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 15/08003-4 - Abordagem de redes complexas em e-Science e dados dinâmicos
• Beneficiário: Filipi Nascimento Silva
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 14/20830-0 - Modelagem e reconhecimento de padrões em textos com redes complexas
• Beneficiário: Diego Raphael Amancio
• Linha de fomento: Auxílio à Pesquisa - Regular
• Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
• Beneficiário: Roberto Marcondes Cesar Junior
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 16/19069-9 - Classificação de documentos usando informações semânticas em redes complexas
• Beneficiário: Diego Raphael Amancio
• Linha de fomento: Auxílio à Pesquisa - Regular