Arabic word Prediction For Next and Previous Word Using Bert & CBOW Algorithms

One application of Natural Language Processing (NLP) is Next Word Prediction, also known as Language Modeling. This process involves predicting the most likely word to follow in a given sentence based on the preceding context. It has numerous widely used applications, like auto-correct, which is mostly used in emails and messages. It can also be used in Microsoft Word or Google searches to predict the next word based on past searches or global queries. The goal of Natural Language Generation (NLG) is to create language that is human-interpretable and natural. Users find text generation, and next-word prediction in particular, convenient as it makes typing faster and error-free. Consequently, an essential analysis topic for all languages is a personalized text prediction system. This paper suggests a novel approach for predicting the following word in a Arabic sentence. It is possible to minimize the total number of keystrokes a user makes by anticipating the next word in a sequence. In this work, Bert algorithm and Continuous Bag of Words(CBOW) are proposed to predict the next word in Arabic language, and predict the previous word. The Bert Algorithm is achieved the best accuracy , 90% for next word prediction, and 80% for previous word prediction . And, Continuous Bag of Words(CBOW) is achieved the best accuracy , 100% for next word prediction, and 100% for previous word prediction.