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Network Embedding

Representation Learning › Network Embedding 0 평가 기록 0 datasets

Network Embedding, also known as "Network Representation Learning", is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding should preserve the structure of the graph. The vectors can then be used as input to various network and graph analysis tasks, such as link prediction

<span class="description-source">Source: Tutorial on NLP-Inspired Network Embedding </span>

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