Turkish News Articles Categorization Using Convolutional Neural Networks and Word2Vec

In this study, a text classification study on the Turkish Text Classification 3600 (TTC-3600) dataset was conducted using Convolutional Neural Networks (CNN) and Word2Vec method and compared with the previous study using the same dataset. In the study, two different CNN s were trained and tested on the TTC-3600 raw and stuck with Zemberek software. CNN and Word2Vec method showed better performance (93.3% accuracy) than classical statistical and machine learning based classification algorithms. Due to the limited number of natural language processing operations in Turkish and the limited feature extraction methods in this area, the accuracy of the CNN models has increased by allowing the semantic values of the words to be included in the classification with the pre-trained Word2Vec network