Our method is based on the observation that there is a tradeoff between accurately modelling similarity in a vector space, and faithfully modelling features as directions.
if o is the vector representation of a given object then we can think of the dot product v f • o as the value of object o for feature f , and in particular, we take to mean that o 2 has the feature f to a greater extent than o 1 .