The chatbot is designed to respond to users with automated responses with respect to the content provided by the user. But the question arises when the user provides a free text which is a synonym of required content or part of the content for the chatbot to understand. In this case most of the Chatbot models using huge libraries which has a large number of samples and require more computational time and storage. Keyword detection methods with a huge amount of data are suitable for most applications but chatbots were designed for specific tasks, for example, ordering food, customer support for the specific application, etc., so these types of chatbots don’t need huge training data. In this paper, we conducted a performance evaluation of different sets and sizes of samples based on certain keywords specifically used for the closed domain chatbot. In this research, we used Movielens 20M dataset which provides tag assignments between movies and unique tags. We used Deep Learning methods in this keyword extraction model.
Chatbots are computer programs that execute protocols for supporting human-machine conversations and perform various functions such as searching the web, ordering food, making appointments, and many more. To facilitate timely responses and actions, and enable interactive human-like conversations, chatbots require Natural Language Processing (NLP) to understand user's messages and respond appropriately. NLP is an area of computer science and artificial intelligence concerned with the interactions between computers and human languages. Google Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Dash Messaging is a smart chatbot platform that enables creation of chatbots based on the provided protocol for long-term conversations. In this paper, we discuss how to integrate Google Dialogflow NLP service to a case study chatbot launched with our Dash Messaging platform.