Sallam Abualhaija and Karl-Heinz Zimmermann
Word sense disambiguation is the problem of finding the most likely senses for a sequence of words in a given context. Disambiguation is a major step in most of the text applications. However, the meanings of the words are highly dependent on the domain of the text. Recently, word sense disambiguation is being addressed as an optimization problem. For this, metaheuristics like simulated annealing and D-Bees are developed. In this paper, we try to answer the question about the compatibility of general domain algorithms to solve specific domain word sense disambiguation. For this, we propose two variants of the D-Bees algorithm to include the domain information into the disambiguation process. The concepts proposed in this paper are general and can be adapted to other algorithms. It will be concluded that the D-Bees algorithm is suitable for solving specific domain word sense disambiguation. It has a robust performance in general and achieves competitive results compared with the simulated annealing method for different datasets.
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