Abstract:

As the number of services are increasing each passing day, the number of queries related to a particular service is also increasing rapidly. To provide solutions to these queries the companies are hiring a huge number of employees that can work as customer support. But this process of providing solution to the customer’s query is very slow for customer and expensive for company. To curb this problem there should be a solution feasible and accessible to everyone. The objective of our project is to provide solution to such problem. The proposed idea is to create a customer support chatbot that responds to the request made by the customer by searching the DB for solutions. The chatbot should be capable enough to interpret to all queries of the customers, analyze them and understand the intent of the queries. If the best solution is found then Chatbot will directly provide the solution to the customer's queries. If no solution is found, then chatbot will send the problem to the Support Staff available to interpret the query and provide a better solution by interacting with the customer. The solutions provided would get updated in the database wherein the chatbot shall be prepared to handle similar queries in future. The proposed idea can be summarized as a customer supports chatbot that performs to accept customer’s query and to give appropriate solution provided in the DB. If solution to the query is not available then redirect the customer to the customer support.
Keywords: NLP (Natural language processing),Token frequency vectorizer(TFV),Machine learning(ML), chatbot

INTRODUCTION:

Chat bots or Virtual Assistants have been designed to simplify the interaction between computers and humans and have hit the market. A chatbot is software that uses artificial intelligence (AI) that can converse (or chat) with a user in natural language via virtual chat rooms, websites, mobile apps and messaging applications or through the telephone. Chatbots are often referred to as one of the most promising and advanced form of interaction between machines and humans. Although, from a technological perspective, a chatbot can only represent the evolution of a Question Answering system based on Natural Language Processing (NLP). Generating responses to user queries in human like natural language is one of the most common examples of Natural Language Processing leveraging in various enterprises’ end-use applications. Chatbot applications slick interactions between services and people, improving customer experience. Simultaneously, chatbots offer companies various opportunities to enhance the customer’s loyalty and ensure operational efficiency by minimizing the surplus cost of customer service. Chatbot solutions have to effectively perform both of the tasks for successful execution. Human support plays a vital role here: Irrespective of the kind of approach and the platform, human intervention plays a crucial role in training, optimizing and configuring the chatbot system. There are two different tasks which form the basis of a chatbot are User Request Analysis and Returning the response.