VERSE: Versatile Graph Embeddings from Similarity Measures

    WWW '18: The Web Conference 2018 Lyon France April, 2018, pp. 539-548, 2018.

    Cited by: 47|Bibtex|Views2|Links
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    Abstract:

    Embedding a web-scale information network into a low-dimensional vector space facilitates tasks such as link prediction, classification, and visualization. Past research has addressed the problem of extracting such embeddings by adopting methods from words to graphs, without defining a clearly comprehensible graph-related objective. Yet, ...More

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