Brown clustering

Brown clustering is a hard hierarchical agglomerative clustering problem based on distributional information proposed by Peter Brown, Vincent Della Pietra, Peter deSouza, Jennifer Lai, and Robert Mercer. It is typically applied to text, grouping words into clusters that are assumed to be semantically related by virtue of their having been embedded in similar contexts.