Multiview Translation Learning for Knowledge Graph Embedding
نویسندگان
چکیده
منابع مشابه
Locally Adaptive Translation for Knowledge Graph Embedding
Knowledge graph embedding aims to represent entities and relations in a large-scale knowledge graph as elements in a continuous vector space. Existing methods, e.g., TransE and TransH, learn embedding representation by defining a global margin-based loss function over the data. However, the optimal loss function is determined during experiments whose parameters are examined among a closed set o...
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Knowledge graph embedding refers to projecting entities and relations in knowledge graph into continuous vector spaces. State-of-the-art methods, such as TransE, TransH, and TransR build embeddings by treating relation as translation from head entity to tail entity. However, previous models can not deal with reflexive/one-to-many/manyto-one/many-to-many relations properly, or lack of scalabilit...
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ژورنال
عنوان ژورنال: Scientific Programming
سال: 2020
ISSN: 1058-9244,1875-919X
DOI: 10.1155/2020/7084958