ADCSA-WSD: Adapted Discrete Crow Search Algorithm for Word Sense Disambiguation

In the field of natural language processing, semantic disambiguation words is beneficial to several applications, which helps us identify correct meaning a word or sequence according given context. It can be formulated as combinatorial optimization problem where goal find set meanings that contribute improving relationship between target words. The Crow Search Algorithm (CSA) nature-inspired algorithm. mimics food foraging behavior crow birds and their social interaction. CSA deal with both continuous discrete problems. this paper, Word Sense Disambiguation (WSD) modelled by nature problem. For propose version has been adapted for solving WSD DCSA-based approach proposed called ADCSA-WSD. evaluated compared state-of-the-art approaches using three well-known benchmark datasets (SemCor 3.0, SensEval-02, SensEval-03). Experimental results show ADCSA-WSD performing better than other approaches.