This measure is based on Lin's information-theoretic similarity theorem (Lin 1997 The similarity between A and B is measured by the ratio between the amount of information needed to state the commonality of A and B and the information needed to fully describe what A and B are.
in our application, if T(w) is the set of features f such that i(w, f ) is positive, then the similarity between two words, w and n, is due to this choice of dss and the openness of the domain, we restrict ourselves to only considering words with a total feature frequency of at least 10.