Research on HMM based link prediction method in heterogeneous network
In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-05-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022095/ |
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| _version_ | 1841539999176065024 |
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| author | Rong QIAN Jianting XU Kejun ZHANG Hongyu DONG Fangyuan XING |
| author_facet | Rong QIAN Jianting XU Kejun ZHANG Hongyu DONG Fangyuan XING |
| author_sort | Rong QIAN |
| collection | DOAJ |
| description | In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM<sup>(1)</sup>) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM<sup>(2)</sup>) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data. |
| format | Article |
| id | doaj-art-de8744dc5b304c65a36d165edd94c47d |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-05-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-de8744dc5b304c65a36d165edd94c47d2025-01-14T06:29:58ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-05-014321422559395880Research on HMM based link prediction method in heterogeneous networkRong QIANJianting XUKejun ZHANGHongyu DONGFangyuan XINGIn order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM<sup>(1)</sup>) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM<sup>(2)</sup>) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022095/heterogeneous networklink predictionhidden Markov modelclusteringmaximum entropy |
| spellingShingle | Rong QIAN Jianting XU Kejun ZHANG Hongyu DONG Fangyuan XING Research on HMM based link prediction method in heterogeneous network Tongxin xuebao heterogeneous network link prediction hidden Markov model clustering maximum entropy |
| title | Research on HMM based link prediction method in heterogeneous network |
| title_full | Research on HMM based link prediction method in heterogeneous network |
| title_fullStr | Research on HMM based link prediction method in heterogeneous network |
| title_full_unstemmed | Research on HMM based link prediction method in heterogeneous network |
| title_short | Research on HMM based link prediction method in heterogeneous network |
| title_sort | research on hmm based link prediction method in heterogeneous network |
| topic | heterogeneous network link prediction hidden Markov model clustering maximum entropy |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022095/ |
| work_keys_str_mv | AT rongqian researchonhmmbasedlinkpredictionmethodinheterogeneousnetwork AT jiantingxu researchonhmmbasedlinkpredictionmethodinheterogeneousnetwork AT kejunzhang researchonhmmbasedlinkpredictionmethodinheterogeneousnetwork AT hongyudong researchonhmmbasedlinkpredictionmethodinheterogeneousnetwork AT fangyuanxing researchonhmmbasedlinkpredictionmethodinheterogeneousnetwork |