Identifying communities and key vertices by reconstructing networks from samples.
Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample "hidden" populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, esp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3622610?pdf=render |
| _version_ | 1811338281550348288 |
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| author | Bowen Yan Steve Gregory |
| author_facet | Bowen Yan Steve Gregory |
| author_sort | Bowen Yan |
| collection | DOAJ |
| description | Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample "hidden" populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network. |
| first_indexed | 2024-04-13T18:08:33Z |
| format | Article |
| id | doaj.art-bf3d7073f5804cd0a9a316541288187a |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-13T18:08:33Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-bf3d7073f5804cd0a9a316541288187a2022-12-22T02:35:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0184e6100610.1371/journal.pone.0061006Identifying communities and key vertices by reconstructing networks from samples.Bowen YanSteve GregorySampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample "hidden" populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network.http://europepmc.org/articles/PMC3622610?pdf=render |
| spellingShingle | Bowen Yan Steve Gregory Identifying communities and key vertices by reconstructing networks from samples. PLoS ONE |
| title | Identifying communities and key vertices by reconstructing networks from samples. |
| title_full | Identifying communities and key vertices by reconstructing networks from samples. |
| title_fullStr | Identifying communities and key vertices by reconstructing networks from samples. |
| title_full_unstemmed | Identifying communities and key vertices by reconstructing networks from samples. |
| title_short | Identifying communities and key vertices by reconstructing networks from samples. |
| title_sort | identifying communities and key vertices by reconstructing networks from samples |
| url | http://europepmc.org/articles/PMC3622610?pdf=render |
| work_keys_str_mv | AT bowenyan identifyingcommunitiesandkeyverticesbyreconstructingnetworksfromsamples AT stevegregory identifyingcommunitiesandkeyverticesbyreconstructingnetworksfromsamples |