Quick Overview
- A new global logbilinear regression model that combines the advantages of the two major model families in the literature: global matrix factorization and local context window methods.
- The model efficiently leverages statistical information by training only on the nonzero elements in a word-word co-occurrence matrix, rather than on the entire sparse matrix or on individual context windows in a large corpus.
Resources