Constructing Fuzzy Relations fromWordNet forWord Sense Disambiguation

In this work, the problem of word sense disambiguation is formulated as a problem of imprecise associations between words and word senses in a textual context. The approach has two main parts. Initially, we consider that for each sense, a fuzzy set is given that provides the degrees of association between a number of words and the sense. An algorithm is provided that ranks the senses of a word in a text based on this information, effectively leading to word sense disambiguation. In the second part, a method based on WordNet is developed that constructs the fuzzy sets for the senses (independent of any text). Algorithms are provided that can help in both understanding and implementation of the proposed approach. Experimental results are satisfactory and show that modeling word sense disambiguation as a problem of imprecise associations is promising