International Research Journal of Engineering and Technology (IRJET) Volume: 09 Issue: 05 | May 2022
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
AI and Web-Based Interactive College Enquiry Chatbot Akshada Phalle1, Saniya Kadam1, Sakshi Sonphule1, Ila Savant2 1Department
of Computer Engineering, Marathwada Mitra Mandal’s College of Engineering, Maharashtra, India Professor, Department of Computer Engineering, Marathwada Mitra Mandal’s College of Engineering, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------2Assistant
Abstract – A chatbot is often described as the most
outpaces resources. Instead of waiting on hold, an enquirer can get answers to his/her questions in real time. This virtual assistant could provide valuable help to college institutions, especially during the admission season. In most colleges, faculties have to devote their time in the admission cells to answer the questions of concerned parents about a college. These queries, though important, are mostly redundant. Thus, we have proposed a web-based college enquiry chatbot that could be integrated with the college's website that could handle all these questions from various departments to placement cells to hostels and so on at a single click from a user. It allows the users to type their query manually or to click on a button of their choice in case they are unsure about their actual doubt. The system would contain information from the official website, except the user won't have to navigate to multiple pages just to know the cut-off for a particular department. Furthermore, for those who do not have the time to actually visit the college website, we have also proposed integration with the messaging application, Telegram which provides users with the opportunity to look back to their previous conversations with the bot, an addition to the web version.
advanced and promising expression of interaction between humans and machines. These digital assistants streamline the interactions between people and services with less human interaction. This is proved as to be a boon during the COVID-19 pandemic when people could no longer visit information desks to get their queries answered. Admission season is arguably the busiest time for a college office. Concerned parents flock the enquiry desks with inquiries about the college. These questions are repetitive and one can use a virtual agent for these doubts which would free the office personnel to handle other issues. This paper proposes a college enquiry chatbot based on Python's chatbot framework, Rasa. Rasa is an open source chatbot framework based on machine learning. With its help, one can easily create highly accurate chatbots and integrate them with websites and messaging applications such as WhatsApp, Facebook, Telegram, etc. The proposed chatbot could handle manually typed as well as rich responses generated by clicking on a payload. It could be integrated with the college website by adding a widget and deployed as on the messaging application, Telegram.
2. MATHEMATICAL MODEL
Keywords: Conversational AI, Natural Language Processing, Human Computer Interaction, Chatbot, College Enquiry Chatbot, Rasa, Rasa X, Python, Telegram Chatbot
Rasa NLU internally uses the following two algorithms for entity extraction:
1. INTRODUCTION
1: Bag of words (BoW) is one of the famous methods for extracting the characteristics from conversations so that it can be used in building models for a machine learning algorithm. It is a representation of words which includes two main things, a document of known words and the frequency of known words. It can simply be simple or complex depending upon the complexity of creating the vocabulary of known words and the circumstance of known words. It follows the succeeding steps
Most websites today be it real-estate, educational institutions, financial firms have a dedicated page for contact information in case a visitor has questions. The problem with this traditional form of online communication is that visitors have to contact help desks only within a stipulated time even if the query is trivial. In rush hours, most people have to be kept on hold in case of limited human resources. Although this is unavoidable, it may leave clients dissatisfied and sully a company's image. This is where conversational AI comes into the picture in the form of chatbots. An artificial conversation entity called chatbot system uses conversational Artificial Intelligence (AI) to simulate a dialogue. It uses rule-based language applications to perform live chat functions in response to real –time user interactions. It removes barriers to customer support that can occur when demand
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a): Collecting the data which could be any input data taken from the user, we can treat each and every line as a different document. b): Designing the vocabulary where we gather the list of all the unique words and discarding case sensitive and punctuation and put that into the model vocabulary.
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