Knowledge Base Completion with Out-of-Knowledge-Base Entities: A Graph Neural Network Approach
نویسندگان
چکیده
منابع مشابه
Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach
Knowledge base completion (KBC) aims to predict missing information in a knowledge base. In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC: how to answer queries concerning test entities not observed at training time. Existing embedding-based KBC models assume that all test entities are available at training time, making it unclear how to obtain embeddings for new...
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ژورنال
عنوان ژورنال: Transactions of the Japanese Society for Artificial Intelligence
سال: 2018
ISSN: 1346-0714,1346-8030
DOI: 10.1527/tjsai.f-h72