When convolutional network meets temporal heterogeneous graphs: an effective community detection method
Community detection has long been an important yet challenging task to analyze complex networks with a focus on detecting topological structures of graph data. Essentially, real-world graph data is generally heterogeneous which dynamically varies over time, and this invalidates most existing communi...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/172861 |