International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
www.irjet.net
AI CHAT BOT USING SHAN ALGORITHM 1. Mrs. S. Nandini (Ph.D)1, A.Nawas Hussain2, B.S. Haran Pranav3, A. L. Abdul Vahith4, J. Samuel George5 1 Professor of Department of Information Technology, Meenakshi College of Engineering, Chennai, Tamil Nadu,
India
2,3,4,5 Student of Department of Information Technology, Meenakshi College of Engineering, Chennai, Tamil Nadu,
India ---------------------------------------------------------------------***--------------------------------------------------------------------connected into a variety of platforms, such as websites, Abstract-
messaging applications, and social networking platforms, allowing users to interact with businesses or services in a seamless and convenient manner. They can also handle many chats at the same time, decreasing human agents' workload.
Letters dominated previous communication. Then, when telephones and, later, mobile phones became more widespread, voice chats took over as the major mode of communication. In many cases, a chatbot can be useful in providing services. These services range from weather forecasts to the option to purchase a new laptop, smartphone, or anything in between. They also provide life-saving health alarms. Numerous big firms, like Google (Google Assistant), Amazon (Alexa), Microsoft (Cortana), and Oracle, are investing substantial time and resources in the research of personal assistants. The development of a chat-bot would cover the following topics: Image recognition with Custom Vision services is utilised with Azure Bot Architecture. We present a SHAN algorithm that combines NLP, RNN, and LSTM.
1.1 Existing System The purpose of a chatbot system is to provide a seamless and efficient means of communication between humans and computers. The system is designed to simulate a human conversation, where the user can input their query or request in natural language, and the chatbot responds with relevant information or assistance [1]. To achieve this goal, the chatbot system's architecture integrates a language model and computational algorithm, which work together to process and interpret the user's input. The language model allows the chatbot to understand and generate natural language responses, while the computational algorithm enables the chatbot to access and retrieve information from various sources to provide accurate and relevant responses to the user.
Keywords—azure bot, NLP, RNN, SHAN ALGO 1.INTRODUCTION: In our daily interactions with friends, family, and co workers, we learn about the context of the topic being discussed. When someone states they are reading a book, you might inquire about the author or whether they enjoy the book rather than asking if they have read any other books. You give the greatest response you can at the time. A chatbot is a piece of software that mimics human communication through text or voice exchanges. It is intended to automate processes and give people information.
One of the key benefits of using a chatbot system is its accessibility. Anyone, from employees to the general public, can freely upload their queries and receive immediate responses. This makes the chatbot system a useful tool for businesses and organizations that want to provide efficient customer service or streamline their internal communication processes. Additionally, the use of chatbots can also reduce the workload of human customer service representatives, allowing them to focus on more complex tasks that require human intervention.
Various platforms, including websites, messaging services, and mobile applications, can incorporate chatbots. An AI chatbot is a computer programme that simulates human-like discussions with people using textbased or voice-based interfaces. These chatbots can be used for a wide range of applications, including customer service, virtual assistants, and even entertainment. To interpret and respond to user inputs, AI chatbots employ natural language processing (NLP) and machine learning algorithms. They are trained on massive volumes of data and are able to learn from user interactions, allowing them to improve their responses over time. Chatbots can be
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1.2 Proposed System The AIML-based bots have been popularly used in the past, other algorithms can also be implemented in chatbot systems to provide improved functionality and performance. For instance, advanced machine learning algorithms such as deep learning models can be used to improve the accuracy of the chatbot's responses.
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