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Disambiguating Arabic Words According to Their Historical Appearance in the Document Based on Recurrent Neural Networks

How can we determine the semantic meaning of a word in relation to its context of appearance? We eventually have to grabble with this difficult question, as one of the paramount problems of Natural Language Processing (NLP). In other words, this issue is commonly defined as Word Sense Disambiguation (WSD). The latter is one of the crucial difficulties within the NLP field. In this respect, word vectors extracted from a neural network model have been successfully applied for resolving the WSD problem. Accordingly, this article presents an unprecedented method to disambiguate Arabic words according to both their contextual appearance in a source text and the era in which they emerged. In fact, in the few previous decades, many researchers have …

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