Streaming networks sampling using top-K networks
Streaming networks sampling using top-K networks
dc.contributor.author | Rui Portocarrero Sarmento | en |
dc.contributor.author | Mário Miguel Cordeiro | en |
dc.contributor.author | João Gama | en |
dc.date.accessioned | 2017-11-23T11:32:17Z | |
dc.date.available | 2017-11-23T11:32:17Z | |
dc.date.issued | 2015 | en |
dc.description.abstract | The combination of top-K network representation of the data stream with community detection is a novel approach to streaming networks sampling. Keeping an always up-to-date sample of the full network, the advantage of this method, compared to previous, is that it preserves larger communities and original network distribution. Empirically, it will also be shown that these techniques, in conjunction with community detection, provide effective ways to perform sampling and analysis of large scale streaming networks with power law distributions. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/3788 | |
dc.identifier.uri | http://dx.doi.org/10.5220/0005341402280234 | en |
dc.language | eng | en |
dc.relation | 5120 | en |
dc.relation | 5880 | en |
dc.relation | 4223 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Streaming networks sampling using top-K networks | en |
dc.type | conferenceObject | en |
dc.type | Publication | en |
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