A Learning-Classification Based Appro Word Prediction

Word prediction is an important NLP problem in which we want to predict the correct % Word completion utilities, predictive text entry systems, writing aids, and language translation are prediction applications. This paper presents a new word prediction approach based on context features The proposed method casts the problem as a learning-classification task by training word p discriminating features selected by various feature selection techniques. The contribution of this work presenting this problem, and the unique combination of a top performer in machine learning, svm selection techniques MI, X2, and more. The method is implemented and evaluated using several data results show clearly that the method is effective in predicting the correct words by utilizing sma, achieved impressive results, compared with similar work; the accuracy in some experiments ap predictions.