… or classification process of the text data. The first stage is for feature extraction of the text …
stage we used the NMF algorithm for classification of the text documents. We normalize the …

… The following two subsections describe how we apply CNN to extract higher-level
sequences of word features and LSTM to capture long-term dependencies over window feature …

… Text classification research started from design the best feature extraction method to
choose the best classifiers. Almost all techniques of text classification based on words [5]. For …

… For MLP neural network, we noticed that the overall F1 measure values for Arabic text
classification increase and become more stable when we use SVD as features extraction …

… vectors: for example biosequences, images, graphs and text documents. For such datasets,
the construction of a feature extraction … This feature extraction process not only requires …

… the features on both … text classification, and shown more significant progress compared
with BoW models. The challenge for textual modeling is how to capture features for different text …

… and terms frequency metrics and machine learning classification. We investigate 2 different
features extraction techniques and 6 different machine learning classification techniques. …

… Naïve Bayes is a machine-learning algorithm, which is frequently used for text classification
problems. It is computationally very efficient and easy to use. The Naïve Bayes assumption is …

… Therefore, this paper proposes a deep learning based text classification feature extraction
… of text classification, and expounds the definition, method and process of text classification. …

… feature extraction model to over-sample and expand the number of samples to deal with the
problem of imbalanced text data from the angle of text data … on other text classification tasks. …