Description
Automated ChatBot for College
Abstract: Automated ChatBot for College – As we all know, individuals all around the world strive to keep up with our fast-paced environment. However, as a result of this, each individual is coping with a variety of health difficulties, one of the most well-known of which is depression or stress, which can lead to death or other heinous acts. These irregularities are known as Bipolar disorder, and they can be cured by following a treatment plan recommended by doctors. For this study, data from working people were collected, which included a variety of questions for melancholy identification, and the dataset was then run through certain machine learning algorithms. In comparison to the other algorithms, the Random Forest method has the highest accuracy of 87.02 percent.
An existing model of the system:-
In the earlier days, students had to visit the college to enquire about details like courses, fee structure, admission process and other information about the college, which is a tiresome process as well as the long process for both parents as well as students. Nowadays there are many changes occurred in the Education system with help of advanced technology. Everything is happening over the internet without any trouble. In those days for enquiring about courses, we have to visit the college, but as the days are passing away its completely changed. Collecting the course details, fee structure manually will be a hectic procedure and it also needs manpower. For reducing that manpower and avoid such difficulties and time consuming many devices or systems emerged day by day.
Proposed model of the system:-
Automated ChatBot for College – A Student Chabot project could be a retrieval-based chatbot that uses AI concepts to possess conversations with humans. Once ever a user asks any question, the bot can first analyze the request, build a response and send it back to the utilization. The chatbot can break down the user sentence into 2 things: intent and an entity. A retrieval-based chatbot is one that functions are predefined input patterns and set responses. Once the question is entered, the chatbot uses a heuristic approach to deliver a suitable response. The retrieval-based model is extensively used to design goal destined chatbots with bespoken options just like the flow and tone of the bot to reinforce the client’s expertise. ChatBots use pattern matching to classify the text and produce a suitable or best response for the clients. A customary structure of those patterns is “Artificial Intelligence Markup Language” (AIML). The planned System could be a net application that has answers to the queries provided by the scholar or the user. Users can just question through the chatbot that is used for chatting. Students can chat in any format there isn’t any specific format the user must follow. The answers are applicable to what the user queries. If the answers are found to be invalid or not accessible, then those queries are held on to the unanswered table that’s basically created by the admin. Later those queries will be updated by the admin, simply just in case of urgency we are providing a message that “our representatives can get to bear with you shortly”. This could be displayed once aggregating the desired data from the user. Admin can browse invalid answers through the portal via login System, it’s going to permit the admin to get rid of the invalid answer conjointly as in updating the acceptable answer for the question raised by the user. The User can raise any college connected activities through the system. The user does not have to be compelled to personally move to the college for inquiry. The System analyzes the question then answers the user. The system answers the query as if it’s answered by the real person. The system replies with the assistance of a decent Graphical interface that suggests that as if a real person is rebuking the user. The user can question concerning the college-connected activities online with the help of this net application. This technique helps the scholar to be updated concerning the faculty-related information.
System architecture:-
System requirements:-
Hardware:-
Operating system Windows 7,8,10(32-bit and 64 bit)
RAM- 4GB
Software:-
Anaconda navigator software, jupyter notebook editor window, python language.
Modules and methodologies:-
Dataset collection
Dataset preprocessing
Feature extraction
Evaluation metrics model
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