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Reconfiguration and Search of Social Networks
Social networks tend to exhibit some topological characteristics different from regular networks and random networks, such as shorter average path length and higher clustering coefficient, and the node degree of the majority of social networks obeys exponential distribution. Based on the topological...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881678/ https://www.ncbi.nlm.nih.gov/pubmed/24574861 http://dx.doi.org/10.1155/2013/391782 |
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author | Zhang, Lianming Peng, Aoyuan Yu, Jianping |
author_facet | Zhang, Lianming Peng, Aoyuan Yu, Jianping |
author_sort | Zhang, Lianming |
collection | PubMed |
description | Social networks tend to exhibit some topological characteristics different from regular networks and random networks, such as shorter average path length and higher clustering coefficient, and the node degree of the majority of social networks obeys exponential distribution. Based on the topological characteristics of the real social networks, a new network model which suits to portray the structure of social networks was proposed, and the characteristic parameters of the model were calculated. To find out the relationship between two people in the social network, and using the local information of the social network and the parallel mechanism, a hybrid search strategy based on k-walker random and a high degree was proposed. Simulation results show that the strategy can significantly reduce the average number of search steps, so as to effectively improve the search speed and efficiency. |
format | Online Article Text |
id | pubmed-3881678 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38816782014-02-26 Reconfiguration and Search of Social Networks Zhang, Lianming Peng, Aoyuan Yu, Jianping ScientificWorldJournal Research Article Social networks tend to exhibit some topological characteristics different from regular networks and random networks, such as shorter average path length and higher clustering coefficient, and the node degree of the majority of social networks obeys exponential distribution. Based on the topological characteristics of the real social networks, a new network model which suits to portray the structure of social networks was proposed, and the characteristic parameters of the model were calculated. To find out the relationship between two people in the social network, and using the local information of the social network and the parallel mechanism, a hybrid search strategy based on k-walker random and a high degree was proposed. Simulation results show that the strategy can significantly reduce the average number of search steps, so as to effectively improve the search speed and efficiency. Hindawi Publishing Corporation 2013-12-18 /pmc/articles/PMC3881678/ /pubmed/24574861 http://dx.doi.org/10.1155/2013/391782 Text en Copyright © 2013 Lianming Zhang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Lianming Peng, Aoyuan Yu, Jianping Reconfiguration and Search of Social Networks |
title | Reconfiguration and Search of Social Networks |
title_full | Reconfiguration and Search of Social Networks |
title_fullStr | Reconfiguration and Search of Social Networks |
title_full_unstemmed | Reconfiguration and Search of Social Networks |
title_short | Reconfiguration and Search of Social Networks |
title_sort | reconfiguration and search of social networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881678/ https://www.ncbi.nlm.nih.gov/pubmed/24574861 http://dx.doi.org/10.1155/2013/391782 |
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