Application of Support Vector Machine Methods in Classification of Customer Communications Data

The paper used automatic information extraction technique, text classification by SVM (Support vector machine) method, combined with Vietnamese word separation technique and natural language processing. Application results of the research used in extracting information, collecting user feedback from e-commerce websites, social networking sites providing businesses with useful information from contributing users in order to build an effective business strategy. The main contributions of this paper are the following: • Apply the BiGAN, the ability of the model to learn mutually coherent inference and generation networks through the inspections of model samples and reconstructions and confirm the usefulness of the learned representations by obtaining a performance competitive with state-of-the-art on Motorbike Generator task. • Improves learning for BiGAN outperforming several state-of-the-art GAN methods training on motorbike dataset by a few techniques such as preprocessing data, data augmentation and hyperparameter tuning.