In the distribution-based feature representation, we take each target noun in turn and compare its amalgamated value for each unit feature with (a) the values for other target nouns, and (b) the value of other unit features within that same feature cluster.
we focus on the relative prominence of features globally within the corpus and locally within each feature cluster.