Using Machine Translators in Textual Data Classification
In this paper, the effect of machine translators in the textual data classification is examined by using supervised classification methods. The developed system first analyzes and classifies an input text in one language, and then analyzes and classifies the same text in another language generated by machine translators from the input text. The obtained results are compared to measure the effect of the translators in textual data classification. The performances of the classification method used in this study are also measured and compared. The classification process can be described as training data preparation, feature selection, and classification of the input texts with/without translation.