Assamese Word Sense Disambiguation using Cuckoo Search Algorithm

Abstract

Natural language processing is associated with human-computer interaction, where several challenges require natural language understanding. The Word sense disambiguation problem comprises the computational assignment of meaning to a word according to a specific context in which it occurs. There are numerous natural language processing applications, such as machine translation, information retrieval, and information extraction, which require this task which takes place at the semantic level. To solve this problem unsupervised computation proposals can be effective since they have been successfully used for many real-world optimization problems. In this paper, we propose to solve the word sense disambiguation problem using the cuckoo search algorithm in the Assamese language. We illustrate the performance of our algorithm by carrying out experiments on an Assamese corpus. And comparing them against an unsupervised genetic algorithm that is implemented in the Assamese language. Results of the experiment show that the cuckoo algorithm can achieve more precision, recall and F-measure, attaining 87.5, 84, and 85.71 percentages respectively.