Whereas, the goal of using the HSA is to maximize the overall semantic similarity of the set of parsed words. The role of the dependency generator is to parse sentences to obtain their dependency relations. We propose an unsupervised method that exploits knowledge based approaches for word sense disambiguation using Harmony Search Algorithm (HSA) based on a Stanford dependencies generator (HSDG). Practically, any sentence that has been classified as ambiguous usually has multiple interpretations, but just one of them presents the correct interpretation. A sentence is considered ambiguous if it contains ambiguous word(s).
Word Sense Disambiguation (WSD) is the task of determining which sense of an ambiguous word (word with multiple meanings) is chosen in a particular use of that word, by considering its context.
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