{'fraction_non_alphanumeric': 0.016036655211912942, 'fraction_numerical': 0.0, 'mean_word_length': 5.775193798449612, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Improvement of Chatbot in Trading System for SMEs by Using Deep Neural Network

This research presents a method for developing chatbots to serve their users. In general, these chatbots are used for answering questions in many businesses, providing customer information, providing train schedules, helping customer reservations, virtual assistants; serve as call centers to serve ten million customers automatically. A deep learning based conversational artificial intelligence technique was used as tools for learning conversation between machine and customer. In addition, the steps required are the technique used in conjunction with the convolution neural network technique by using Tensorflow training to improve the accuracy of these chatbots. From the experimental results, using deep learning for chatbots learning, the accuracy is better than the traditional model.