Spatio-temporal periodic behavior mining algorithm for social networks

A hierarchical bipartite graph based model and a mining algorithm were presented to obtain the potential spatio-temporal periodic behavior,meanwhile avoided the subset omitting problem in previous schemes.Then the location analysis algorithm was designed to achieve the nearly inimum location dominat...

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Main Authors: Yu-peng HU, Hao LUO, Ya-ping LIN, Zheng QIN, Bo YIN
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2013-01-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/1000-436X(2013)01-0008-11/
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author Yu-peng HU
Hao LUO
Ya-ping LIN
Zheng QIN
Bo YIN
author_facet Yu-peng HU
Hao LUO
Ya-ping LIN
Zheng QIN
Bo YIN
author_sort Yu-peng HU
collection DOAJ
description A hierarchical bipartite graph based model and a mining algorithm were presented to obtain the potential spatio-temporal periodic behavior,meanwhile avoided the subset omitting problem in previous schemes.Then the location analysis algorithm was designed to achieve the nearly inimum location dominating subset,it could monitor the small portion of the locations as early as possible.Finally experiments results show that the algorithms can find out the periodic location set as well as obtain nearly minimum location dominating subset,so as to cover the major portion of objectives using those popular locations.
format Article
id doaj-art-f378d7d6112d460782d5bd447ad46984
institution Kabale University
issn 1000-436X
language zho
publishDate 2013-01-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-f378d7d6112d460782d5bd447ad469842025-01-14T06:34:04ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-01-013481859668050Spatio-temporal periodic behavior mining algorithm for social networksYu-peng HUHao LUOYa-ping LINZheng QINBo YINA hierarchical bipartite graph based model and a mining algorithm were presented to obtain the potential spatio-temporal periodic behavior,meanwhile avoided the subset omitting problem in previous schemes.Then the location analysis algorithm was designed to achieve the nearly inimum location dominating subset,it could monitor the small portion of the locations as early as possible.Finally experiments results show that the algorithms can find out the periodic location set as well as obtain nearly minimum location dominating subset,so as to cover the major portion of objectives using those popular locations.http://www.joconline.com.cn/zh/article/doi/1000-436X(2013)01-0008-11/social networkhierarchical bipartite graphspatio-temporal periodic behavior patternminimum location dominating subset
spellingShingle Yu-peng HU
Hao LUO
Ya-ping LIN
Zheng QIN
Bo YIN
Spatio-temporal periodic behavior mining algorithm for social networks
Tongxin xuebao
social network
hierarchical bipartite graph
spatio-temporal periodic behavior pattern
minimum location dominating subset
title Spatio-temporal periodic behavior mining algorithm for social networks
title_full Spatio-temporal periodic behavior mining algorithm for social networks
title_fullStr Spatio-temporal periodic behavior mining algorithm for social networks
title_full_unstemmed Spatio-temporal periodic behavior mining algorithm for social networks
title_short Spatio-temporal periodic behavior mining algorithm for social networks
title_sort spatio temporal periodic behavior mining algorithm for social networks
topic social network
hierarchical bipartite graph
spatio-temporal periodic behavior pattern
minimum location dominating subset
url http://www.joconline.com.cn/zh/article/doi/1000-436X(2013)01-0008-11/
work_keys_str_mv AT yupenghu spatiotemporalperiodicbehaviorminingalgorithmforsocialnetworks
AT haoluo spatiotemporalperiodicbehaviorminingalgorithmforsocialnetworks
AT yapinglin spatiotemporalperiodicbehaviorminingalgorithmforsocialnetworks
AT zhengqin spatiotemporalperiodicbehaviorminingalgorithmforsocialnetworks
AT boyin spatiotemporalperiodicbehaviorminingalgorithmforsocialnetworks