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Comparative Study ofConvolutional Neural Network with Word Embedding Technique for Text Classification
2019
International Journal of Intelligent Systems and Applications
This paper presents an investigation of the convolutional neural network (CNN) with Word2Vec word embedding technique for text classification. Performance of CNN is tested on seven benchmark datasets with a different number of classes, training and testing samples. Test classification results obtained from proposed CNN are compared with results of CNN models and other classifiers reported in the literature. Investigation shows that CNN models are better suitable for text classification than
doi:10.5815/ijisa.2019.08.06
fatcat:wv7i3y5shzdq7oafcsw3udlhnm