Improving the Accuracy of Customer Service Seq2Seq Chatbots Through Dataset Pruning

Chatbots are extensively needed in customer services to handle customer inquiries, such as tracking orders or providing information about products and services. One of the most reliable implementations of chatbots is using the common architectures of LSTM networks named Seq2Seq networks. The networks are using an encoder and a decoder. Seq2Seq chatbot is a type of chat system that is professional enough to pass the Turing test. The Turing test is a way of deciding the accuracy of the machine by examining its response, it should appear like a human response. In this research, we will introduce a novel architecture that can pass the Turing test. The seq2seq Accuracy is improved by making incremental training to the chatbot. The new proposal provides higher accuracy and high similarity to human chat responses.