Implementation of Service Based Chatbot Using Deep Learning

Abstract

A conversational agent (chatbot) is a software application which provides communication environment for conversation between machine and humans using natural language. The conversation is to be modeled to make it understandable to the machine and also it is an important task in (AI). In the modern digital era the dependency on computer is increasing day by day. One of the challenging tasks that everybody is looking is how to make a machine conversional with the user. Artificial Intelligence helping the developers to make a digital machine more intelligent and it should behave like a human being in understating the user queries and responding to the queries. The chatbot plays the crucial role in conversion with the user. Chatbot is a piece of software which will run on a computer. Normally chatbots are used for understanding the senetences given by the user and provide responses that are relevant to the user sentence that are already defined. In the past, constructing chatbot architectures have relied on rules specified by hand written and predefined templates or simple statistical approaches. With the rise of machine learning, deep learning and neural networks these models were quickly replaced by end-to-end trainable neural networks. Siri by Apple, Cortana by Microsoft, Google Assistant, and Alexa by Amazon are some of the most popular conversational agents today. They can assist user to get directions, check the scores of sports games and pick the phone number in your address book and call the people. But these chatbots give responses to the user from all the fields included when the people are searching for a particular field. So we are going to develop a chatbot for a service based so that it can give accurate results that the user wants and avoid confusion for the user.