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Word Sense Disambiguation (WSD) is the task to determine the sense of anambiguous word in a given context. Previous approaches for WSD have focused onsupervised and knowledge-based methods, but inter-sense interactions patternsor regularities for disambiguation remain to be found. We argue the followingcause as one of the major difficulties behind finding the right patterns: for aparticular context, the intended senses of a sequence of ambiguous words aredependent on each other, i.e. the choice of one word's sense is associated withthe choice of another word's sense, making WSD a combinatorial optimizationproblem.In this work, we approach the interactions between senses of differenttarget words by a Quadratic 0-1 Integer Programming model (QIP) that maximizesthe objective function consisting of (1) the similarity between candidatesenses of a target word and the word in a context (the sense-word similarity),and (2) the semantic interactions (relatedness) between senses of all words inthe context (the sense-sense relatedness).

A Quadratic 0-1 Programming Approach for Word Sense Disambiguation