Enabling Cognitive Intelligence Queries in Relational Databases using Low-dimensional Word Embeddings

23 Mar 2016Rajesh BordawekarOded Shmueli

We apply distributed language embedding methods from Natural Language Processing to assign a vector to each database entity associated token (for example, a token may be a word occurring in a table row, or the name of a column). These vectors, of typical dimension 200, capture the meaning of tokens based on the contexts in which the tokens appear together... (read more)

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