ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine
The problem of community detection has attracted great attentions from various fields and community structure is one of the most important characteristics in complex networks. However, there are few researches on the detection of anti-community structure, where the nodes share no or few connections...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8793055/ |
| _version_ | 1818566038776709120 |
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| author | Qiaoqin Li Yongguo Liu Jiajing Zhu Yonghua Xiao Hao Wu Xiaofeng Liu Zijie Chen Shuangqing Zhai |
| author_facet | Qiaoqin Li Yongguo Liu Jiajing Zhu Yonghua Xiao Hao Wu Xiaofeng Liu Zijie Chen Shuangqing Zhai |
| author_sort | Qiaoqin Li |
| collection | DOAJ |
| description | The problem of community detection has attracted great attentions from various fields and community structure is one of the most important characteristics in complex networks. However, there are few researches on the detection of anti-community structure, where the nodes share no or few connections inside their group they belong to but most of their connections outside. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a great challenge to clinical medication safety, which becomes a serious threat to public health. In this paper, a new ANti-community detection algorithm based on the DEgree and the RATio between the Inner degree and the Outer degree of a Node (ANDERATION), is proposed, in which these two factors are firstly introduced to detect anti-community structure by first creating the initial anti-community structure and then maximizing the objective function. Experimental results on 15 synthetic and 14 real-world networks demonstrate that the proposed algorithm can detect better anti-community structures with less running time than the existing algorithms. By applying ANDERATION to the herb network, we find that it is effective in exploring incompatible herb combinations in TCM. |
| first_indexed | 2024-12-14T01:48:36Z |
| format | Article |
| id | doaj.art-6e1f95ca36bf4de9be8c69d01fb46be6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T01:48:36Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6e1f95ca36bf4de9be8c69d01fb46be62022-12-21T23:21:28ZengIEEEIEEE Access2169-35362019-01-01711397511398710.1109/ACCESS.2019.29342278793055ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese MedicineQiaoqin Li0Yongguo Liu1https://orcid.org/0000-0002-4906-7025Jiajing Zhu2Yonghua Xiao3Hao Wu4Xiaofeng Liu5Zijie Chen6Shuangqing Zhai7Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, ChinaThe problem of community detection has attracted great attentions from various fields and community structure is one of the most important characteristics in complex networks. However, there are few researches on the detection of anti-community structure, where the nodes share no or few connections inside their group they belong to but most of their connections outside. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a great challenge to clinical medication safety, which becomes a serious threat to public health. In this paper, a new ANti-community detection algorithm based on the DEgree and the RATio between the Inner degree and the Outer degree of a Node (ANDERATION), is proposed, in which these two factors are firstly introduced to detect anti-community structure by first creating the initial anti-community structure and then maximizing the objective function. Experimental results on 15 synthetic and 14 real-world networks demonstrate that the proposed algorithm can detect better anti-community structures with less running time than the existing algorithms. By applying ANDERATION to the herb network, we find that it is effective in exploring incompatible herb combinations in TCM.https://ieeexplore.ieee.org/document/8793055/Anti-community detectioncomplex networkincompatibility of herbstraditional Chinese medicine |
| spellingShingle | Qiaoqin Li Yongguo Liu Jiajing Zhu Yonghua Xiao Hao Wu Xiaofeng Liu Zijie Chen Shuangqing Zhai ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine IEEE Access Anti-community detection complex network incompatibility of herbs traditional Chinese medicine |
| title | ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine |
| title_full | ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine |
| title_fullStr | ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine |
| title_full_unstemmed | ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine |
| title_short | ANDERATION: A New Anti-Community Detection Algorithm and its Application to Explore Incompatibility of Traditional Chinese Medicine |
| title_sort | anderation a new anti community detection algorithm and its application to explore incompatibility of traditional chinese medicine |
| topic | Anti-community detection complex network incompatibility of herbs traditional Chinese medicine |
| url | https://ieeexplore.ieee.org/document/8793055/ |
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