Learning embedded representation of a correlation matrix to a network with machine learning

Abstract

System, method, and a computer program product for generating embeddings are provided. A machine learning framework generates a fully connected network from a dataset associated with words. The words correspond to nodes in the fully connected network. The weights are associated with correlations between the nodes and correspond to the links in the fully connected network. The machine learning framework transforms the correlations corresponding to the links into distances. The machine learning framework generates a sparse network from the fully connected network based on the distances. From the sparse network, machine learning framework determines sentence structures by traversing the nodes. Using the sentence structures, the machine learning framework uses a neural network to generate embeddings in the embedded space.