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Statistical measures of word similarity are widely used in many areas of information retrieval and text mining. Among popular word co-occurrence based measures is Pointwise Mutual Information (PMI). Altough widely used, PMI has a well-known tendency to give excessive scores of relatedness to word pairs that involve lowfrequency words. Many variants of it have therefore been proposed, which correct this bias empirically. In contrast to this empirical approach, we propose formulae and indicators that describe the behavior of these variants in a precise way so that researchers and practitioners can make a more informed decision as to which measure to use in different scenarios.

HANDLING THE IMPACT OF LOW FREQUENCY EVENTS ON CO-OCCURRENCE BASED MEASURES OF WORD SIMILARITY - A Case Study of Pointwise Mutual Information