… text feature extraction approaches by analyzing their influence over the accuracy of a
neural network classifier. The TF-IDF feature extraction approach is found to outperform other …

… feature extraction methods, as well [13]. Aside from the ones we named above, there are
many types of feature selection and feature extraction methods … widely known methods, which …

… recommendation, text classification techniques have been … review on feature selection
techniques for text classification. … used in text classification. Then, we review the most popular …

… In this paper, a brief overview of text classification algorithms … text feature extractions,
dimensionality reduction methods, … methods of text classification, such as Rocchio classification. …

… -based approach to document classification is … classification accuracy. Document sets are
represented as graph sets to which a weighted graph mining algorithm is applied to extract …

… feature extraction or by using feature selection. In this paper, we used both feature selection
and feature extraction techniques… by using fewer and more distinctive features, to reduce the …

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 …

… feature representation from big data, including millions of parameters. This thesis outlines the
common methods used in text feature extraction … [85], a novel text classification approach is …

… discusses feature extraction techniques used for text classification as … techniques used as
technology and algorithms that have become more sophisticated to optimize feature extraction…

… Most research in speeding up text mining involves algorithmic improvements to induction
algorithms, and yet for many large scale applications, such as classifying or indexing large …