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arXiv 2102.08014cs.AIcs.LGstat.ML
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Representing Hierarchical Structure by Using Cone Embedding

Keio University(庆应义塾大学)

Daisuke Takehara, Kei Kobayashi

英文摘要:

Graph embedding is becoming an important method with applications in various areas, including social networks and knowledge graph completion. In particular, Poincaré embedding has been proposed to capture the hierarchical structure of graphs, and its effectiveness has been reported. However, most of the existing methods have isometric mappings in the embedding space, and the choice of the origin point can be arbitrary. This fact is not desirable when the distance from the origin is used as an indicator of hierarchy, as in the case of Poincaré embedding. In this paper, we propose cone embedding, embedding method in a metric cone, which solve these problems, and we gain further benefits: 1) we provide an indicator of hierarchical information that is both geometrically and intuitively natural to interpret, and 2) we can extract the hierarchical structure from a graph embedding output of other methods by learning additional one-dimensional parameters.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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