The counts were then transformed into Local Mutual Information (LMI) scores, an association measure that closely approximates the commonly used Log-Likelihood Ratio but is simpler to compute (Evert, 2005).
given a row element r, a column element c and a counting function C(r, c), then where C(r, c) is how many times r cooccurs with c, C(r, * ) is the total count of r, C( * , c) is the total count of c, and C( * , * ) is the cumulative cooccurrence count of any r with any c. The dimensionality of the space was reduced using Singular Value Decomposition (SVD), as in Latent Semantic Analysis and related distributional semantic methods (Landauer and Dumais, 1997;Rapp, 2003;Schütze, 1997).