Research for Practice: Knowledge Base Construction in the Machine-Learning Era.

The article reports on the construction of knowledge bases through the use of deep learning. It presents summaries of three papers on several facets of knowledge base construction: the need for joint learning to prevent error cascades, the weak supervision of training data, and the representation of...

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Detalles Bibliográficos
Publicado en:Communications of the ACM Vol. 61; no. 11; pp. 95 - 98
Autores principales: RATNER, ALEX, RÉ, CHRIS
Formato: Artículo
Publicado: Association for Computing Machinery Nov2018
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:The article reports on the construction of knowledge bases through the use of deep learning. It presents summaries of three papers on several facets of knowledge base construction: the need for joint learning to prevent error cascades, the weak supervision of training data, and the representation of the data both as it is input and output.