… In this paper, a comparative analysis of text classification is … A number of text classifiers are
used in text mining are used … SVM is also compared to other algorithms, but SVM outperforms …

… We highlight the differences between earlier methods and more … fields of text mining and
natural language processing (NLP). … In short, SVMs construct an optimal hyperplane in a simple …

… Text mining is an important part of data mining that organizes … Since this paper deals with
three objectives of comparing the … these tasks are solved by means of the stage of linguistic text …

… classification of emotions in text. The classification algorithm used in this paper is the SVM …
Word2Vec is used in this study because it provides better performance for the semantic task in …

… based on a solid basis of comparison. The performances of the … Text classification (TC) is
defined as a text mining process … To illustrate the optimization behind the SVM model, we start …

… Text mining, as a subfield of data mining, has become … ML, in which an algorithm seeks
for similarities in a data set … by the results (classification accuracy for SVM algorithm was 0.9)…

… As classification algorithms, we exploit SVM, … some important characteristics of the task, in
our case ATC, before given this enriched representation to a strong classifier, in our case, SVM…

… , such as: Visual Text Mining or Text Classification. But … SVM algorithms performed with
respect to the exclusion rate and Missed selected studies rate. For both algorithms, we compared …

… in the field of text mining also known as text categorization [6]. … learning algorithms such as
Support Vector Machine, Neural … This algorithm has more potential in comparison with other …

… algorithms MNB, LR, SVM and RNN Classifier have been used. In this paper, a comparison
has … in the output by the older inputs becomes less and less and thus vanishes and we lose …