A Review of Algorithms, Datasets, and Criteria in Word Sense Disambiguation With a View to its Use in Islamic Texts

Abstract

Most of the words in a natural language are polysemous; it means, they have multiple senses. Word sense disambiguation is the process of determining the exact sense of the polysemous word by analyzing the context in which the word occurs. Word sense disambiguation is one of the fundamental tasks in the field of natural language processing. However, There have been few studies in word sense disambiguation in Persian and Arabic languages. For the above reason and considering the abundance of ambiguous words and phrases in Islamic texts, the need for a special algorithm to help the disambiguation of such texts is felt. The present study attempted to have an overall review of word sense disambiguation approaches, strategies and issues, in order to open the way for future work on the presentation of similar algorithms for Islamic texts. We review approaches such as semi-supervised, unsupervised, supervised and knowledge-based approaches. The best strategy will be introduced, and the state-of-the-art systems related to it will be compared.