The semantic neighborhood of w, denoted by N(w), is defined as the set of all words v which are considered sufficiently similar to w, satisfying sim(w, v) > θ sim , where θ sim is a second empirically determined threshold.
the bootstrapped feature weight, denoted weight B , is then defined by: we identify all words v that are in the semantic neighborhood of w and are also characterized by f , and then sum the values of their similarities to w. Intuitively, summing these similarity values captures simultaneously a desired balance between feature specificity and generality, addressing the observations in the beginning of this section.