Semisupervised Community Preserving Network Embedding with Pairwise Constraints
Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors. These vectors are used as inputs of machine learning algorithms for netw...
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| Hauptverfasser: | , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Wiley
2020-01-01
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| Schriftenreihe: | Complexity |
| Online-Zugang: | http://dx.doi.org/10.1155/2020/7953758 |
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