… In reference [87], this paper proposes a novel hybrid text classification model based on the
deep belief network and softmax regression. The experimental results on Reuters-21578 and …

We describe an approach to text classification that represents a compromise between traditional
word-based techniques and in-depth natural language processing. Our approach uses …

… the performance of classification algorithms using Scopus dataset. In text classification,
classification and feature extraction from the document using extracted features are the major …

… This article reviews and discusses feature extraction techniques used for text classification …
optimize feature extraction. In feature extraction, a specific of words is taken out from text data. …

… features. To the best of our knowledge, we are the first to incorporate global representation
into the extraction procedure of local features for text classification… regions feature extraction …

… before the feature extraction. Since feature extraction in text classification generally results in
… dimension reduction to use classification algorithms efficiently. After dimension reduction, a …

… However, as is common in probabilistic models for text classification tasks, the formula in
Figure 1 makes assumptions about the independence of probabilities which do not hold for …

… schemes for extraction and selection of the features to classify Bangla text documents from
… of text documents consisting of contents from few more domains. Also some standard feature …

… of text classification. First, we cover traditional methods of text classification, such as Rocchio
classification. Next… Furthermore, we discuss two common methods of text feature extraction: …