基于变分推断和元路径分解的异质网络表示方法
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袁铭, 刘群, 孙海超, 谭洪胜
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A Heterogeneous Network Representation Method Based on Variational Inference and Meta-Path Decomposition
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YUAN Ming, LIU Qun, SUN Haichao, TAN Hongsheng
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表2 节点聚类任务的定量结果
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Tab.2 Quantitative results of node clustering tasks
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算法 | DBLP | | AMiner | | Yelp | NMI | ARI | NMI | ARI | NMI | ARI | Deepwalk | 0.5841 | 0.4960 | | 0.3160 | 0.2227 | | 0.2940 | 0.3179 | Node2vec | 0.5401 | 0.4776 | | 0.3081 | 0.2219 | | 0.0105 | 0.0111 | HIN2vec | 0.0124 | 0.0106 | | 0.1670 | 0.0758 | | 0.1353 | 0.1708 | Metapath2vec | 0.6395 | 0.6369 | | 0.2645 | 0.2083 | | 0.3540 | 0.4047 | HERec | 0.6844 | 0.7104 | | 0.3230 | 0.2322 | | 0.3511 | 0.4018 | HAN | 0.5987 | 0.5929 | | 0.0375 | 0.0165 | | 0.3635 | 0.4255 | HetVAErw | 0.7742 | 0.8329 | | 0.3324 | 0.2234 | | 0.3603 | 0.4016 | HetVAEsk | 0.8173 | 0.8664 | | 0.3446 | 0.2321 | | 0.3593 | 0.4097 | HetVAEcon | 0.7826 | 0.8351 | | 0.3239 | 0.2660 | | 0.3416 | 0.3917 | HetVAE | 0.8540 | 0.9016 | | 0.4025 | 0.3798 | | 0.3761 | 0.4399 |
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