A Semantic Community Detection Algorithm Based on Quantizing Progress
The semantic social network is a kind of network that contains enormous nodes and complex semantic information, and the traditional community detection algorithms could not give the ideal cogent communities instead. To solve the issue of detecting semantic social network, we present a clustering com...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/3475458 |
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| _version_ | 1832548842887708672 |
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| author | Xu Han Deyun Chen Hailu Yang |
| author_facet | Xu Han Deyun Chen Hailu Yang |
| author_sort | Xu Han |
| collection | DOAJ |
| description | The semantic social network is a kind of network that contains enormous nodes and complex semantic information, and the traditional community detection algorithms could not give the ideal cogent communities instead. To solve the issue of detecting semantic social network, we present a clustering community detection algorithm based on the PSO-LDA model. As the semantic model is LDA model, we use the Gibbs sampling method that can make quantitative parameters map from semantic information to semantic space. Then, we present a PSO strategy with the semantic relation to solve the overlapping community detection. Finally, we establish semantic modularity (SimQ) for evaluating the detected semantic communities. The validity and feasibility of the PSO-LDA model and the semantic modularity are verified by experimental analysis. |
| format | Article |
| id | doaj-art-b51a9b8d902d45c5a1dff8118f3635c0 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-b51a9b8d902d45c5a1dff8118f3635c02025-02-03T06:12:55ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/34754583475458A Semantic Community Detection Algorithm Based on Quantizing ProgressXu Han0Deyun Chen1Hailu Yang2School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, ChinaThe semantic social network is a kind of network that contains enormous nodes and complex semantic information, and the traditional community detection algorithms could not give the ideal cogent communities instead. To solve the issue of detecting semantic social network, we present a clustering community detection algorithm based on the PSO-LDA model. As the semantic model is LDA model, we use the Gibbs sampling method that can make quantitative parameters map from semantic information to semantic space. Then, we present a PSO strategy with the semantic relation to solve the overlapping community detection. Finally, we establish semantic modularity (SimQ) for evaluating the detected semantic communities. The validity and feasibility of the PSO-LDA model and the semantic modularity are verified by experimental analysis.http://dx.doi.org/10.1155/2019/3475458 |
| spellingShingle | Xu Han Deyun Chen Hailu Yang A Semantic Community Detection Algorithm Based on Quantizing Progress Complexity |
| title | A Semantic Community Detection Algorithm Based on Quantizing Progress |
| title_full | A Semantic Community Detection Algorithm Based on Quantizing Progress |
| title_fullStr | A Semantic Community Detection Algorithm Based on Quantizing Progress |
| title_full_unstemmed | A Semantic Community Detection Algorithm Based on Quantizing Progress |
| title_short | A Semantic Community Detection Algorithm Based on Quantizing Progress |
| title_sort | semantic community detection algorithm based on quantizing progress |
| url | http://dx.doi.org/10.1155/2019/3475458 |
| work_keys_str_mv | AT xuhan asemanticcommunitydetectionalgorithmbasedonquantizingprogress AT deyunchen asemanticcommunitydetectionalgorithmbasedonquantizingprogress AT hailuyang asemanticcommunitydetectionalgorithmbasedonquantizingprogress AT xuhan semanticcommunitydetectionalgorithmbasedonquantizingprogress AT deyunchen semanticcommunitydetectionalgorithmbasedonquantizingprogress AT hailuyang semanticcommunitydetectionalgorithmbasedonquantizingprogress |