Identification of key node groups based on motif structure and degree information
In order to explore the impact of higher-order structures with smaller scales on key node group mining problems and with the goal of optimizing network propagation, a key node group recognition algorithm was proposed based on motif structure and degree information.Firstly, the influence of nodes was...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2024-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024052/ |
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| _version_ | 1841540020457963520 |
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| author | Yunyun YANG Liao ZHANG Hailong YU Li WANG |
| author_facet | Yunyun YANG Liao ZHANG Hailong YU Li WANG |
| author_sort | Yunyun YANG |
| collection | DOAJ |
| description | In order to explore the impact of higher-order structures with smaller scales on key node group mining problems and with the goal of optimizing network propagation, a key node group recognition algorithm was proposed based on motif structure and degree information.Firstly, the influence of nodes was evaluated based on the motif structure, and the core nodes of the motif structure were excavated.Then, the VIKOR method was used to fuse it with degree information.Finally, the seed exclusion algorithm was used to exclude the neighbors of the seed nodes, effectively reducing the problem of influence overlap.Based on the SIR propagation model, six different undirected networks were selected for comparison with four benchmark algorithms.The experimental results show that the proposed algorithm performs better in terms of accuracy and stability. |
| format | Article |
| id | doaj-art-1dea3917e0be4c4192a5b512498e245f |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1dea3917e0be4c4192a5b512498e245f2025-01-14T06:22:00ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-03-014525826959296899Identification of key node groups based on motif structure and degree informationYunyun YANGLiao ZHANGHailong YULi WANGIn order to explore the impact of higher-order structures with smaller scales on key node group mining problems and with the goal of optimizing network propagation, a key node group recognition algorithm was proposed based on motif structure and degree information.Firstly, the influence of nodes was evaluated based on the motif structure, and the core nodes of the motif structure were excavated.Then, the VIKOR method was used to fuse it with degree information.Finally, the seed exclusion algorithm was used to exclude the neighbors of the seed nodes, effectively reducing the problem of influence overlap.Based on the SIR propagation model, six different undirected networks were selected for comparison with four benchmark algorithms.The experimental results show that the proposed algorithm performs better in terms of accuracy and stability.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024052/motifkey node groupinfluence maximization |
| spellingShingle | Yunyun YANG Liao ZHANG Hailong YU Li WANG Identification of key node groups based on motif structure and degree information Tongxin xuebao motif key node group influence maximization |
| title | Identification of key node groups based on motif structure and degree information |
| title_full | Identification of key node groups based on motif structure and degree information |
| title_fullStr | Identification of key node groups based on motif structure and degree information |
| title_full_unstemmed | Identification of key node groups based on motif structure and degree information |
| title_short | Identification of key node groups based on motif structure and degree information |
| title_sort | identification of key node groups based on motif structure and degree information |
| topic | motif key node group influence maximization |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024052/ |
| work_keys_str_mv | AT yunyunyang identificationofkeynodegroupsbasedonmotifstructureanddegreeinformation AT liaozhang identificationofkeynodegroupsbasedonmotifstructureanddegreeinformation AT hailongyu identificationofkeynodegroupsbasedonmotifstructureanddegreeinformation AT liwang identificationofkeynodegroupsbasedonmotifstructureanddegreeinformation |