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Evolving network representation learning based on random walks
Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that can be utilized to perform highly accurate and scalable grap...
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| Pubblicato in: | Appl Netw Sci |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer International Publishing
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7081665/ https://ncbi.nlm.nih.gov/pubmed/32215318 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41109-020-00257-3 |
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