def score_cosine(self, term1, term2, **kwargs):
t1_kde = self.kde(term1, **kwargs)<EOL>t2_kde = self.kde(term2, **kwargs)<EOL>return <NUM_LIT:1>-distance.cosine(t1_kde, t2_kde)<EOL>
Compute a weighting score based on the cosine distance between the
kernel density estimates of two terms.

Args:
    term1 (str)
    term2 (str)

Returns: float