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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

The dynamics of knowledge acquisition via self-learning in complex networks

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Author(s):
Lima, Thales S. [1] ; de Arruda, Henrique F. [1] ; Silva, Filipi N. [2, 3] ; Comin, Cesar H. [4] ; Amancio, Diego R. [1, 3] ; Costa, Luciano da F. [2]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Sao Carlos Inst Phys, BR-13566590 Sao Carlos, SP - Brazil
[3] Indiana Univ, Sch Informat Comp & Engn, Bloomington, IN 47408 - USA
[4] Univ Fed Sao Carlos, Dept Comp Sci, BR-13565905 Sao Carlos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: Chaos; v. 28, n. 8 AUG 2018.
Web of Science Citations: 2
Abstract

Studies regarding knowledge organization and acquisition are of great importance to understand areas related to science and technology. A common way to model the relationship between different concepts is through complex networks. In such representations, networks' nodes store knowledge and edges represent their relationships. Several studies that considered this type of structure and knowledge acquisition dynamics employed one or more agents to discover node concepts by walking on the network. In this study, we investigate a different type of dynamics adopting a single node as the ``network brain.{''} Such a brain represents a range of real systems such as the information about the environment that is acquired by a person and is stored in the brain. To store the discovered information in a specific node, the agents walk on the network and return to the brain. We propose three different dynamics and test them on several network models and on a real system, which is formed by journal articles and their respective citations. The results revealed that, according to the adopted walking models, the efficiency of self-knowledge acquisition has only a weak dependency on topology and search strategy. Published by AIP Publishing. (AU)

FAPESP's process: 17/13464-6 - Modelling citation and information graphs: a complex network approach
Grantee:Diego Raphael Amancio
Support Opportunities: Scholarships abroad - Research
FAPESP's process: 17/09280-7 - Probing the structure and dynamics of information networks
Grantee:Filipi Nascimento Silva
Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 16/19069-9 - Using semantical information to classify texts modelled as complex networks
Grantee:Diego Raphael Amancio
Support Opportunities: Regular Research Grants
FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 15/08003-4 - Complex network approach to e-Science and dynamic datasets
Grantee:Filipi Nascimento Silva
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 15/18942-8 - Associating Complex Networks with Effective Feature Spaces
Grantee:Cesar Henrique Comin
Support Opportunities: Scholarships in Brazil - Post-Doctoral