Due to the increasing demand of transporting huge amount of information generated from various sources such as queries and voice. A Chatbot is an artificial intelligence-powered piece of software in a device. Some of them are Siri, Alexa, Google Assistant etc. Some of the ways in which
Student E Advisor Chatbot
Due to the increasing demand of transporting huge amount of information generated from various sources such as queries and voice. A Chatbot is an artificial intelligence-powered piece of software in a device. Some of them are Siri, Alexa, Google Assistant etc. Some of the ways in which companies are using Chatbots to deliver flight information, to connect customers and their finances and as customer support. Since the bots are designed as conversational and friendly. The Student E-Advisor Chatbot will be embedded in university website, it will handle the queries of students who are getting admission, it will resolve the queries which are entered by the students like getting information about admissions, fee structure, programs departments and faculties. The chatbot will work on the self-base approach and will analysis the queries according to the dataset store in the knowledge database, it will make prediction by comparing and answer to the user on the basis of analysis.
| The Student E-Advisor Chatbot will handle and resolve the queries generated by the students, the bot will produce the result on the basis of analysis and prediction of the knowledge base which is embedded at the backend of the system. The basic purpose of developing the Student E-Advisor Chatbot is to facilitate the fresh students who are getting admission in the university and are not familiar about the university’s structure like admissions, fee, programs offered, departments and faculty. The chatbot will provide the information about the admission date and procedure of admission, fee of various programs and it’s submission, programs that are offered complete information about the duration and semester duration and subjects, the bot will also provide the information about the departments and faculty. There are various informative aspects that will be deal by the bot like Student Services Center (SSC). |
The Student E-Advisor Chatbot will handle and resolve the queries generated by the students, the bot will produce the result on the basis of analysis and prediction of the knowledge base which is embedded at the backend of the system. The basic purpose of developing the Student E-Advisor Chatbot is to facilitate the fresh students who are getting admission in the university and are not familiar about the university’s structure like admissions, fee, programs offered, departments and faculty. The chatbot will provide the information about the admission date and procedure of admission, fee of various programs and it’s submission, programs that are offered complete information about the duration and semester duration and subjects, the bot will also provide the information about the departments and faculty. There are various informative aspects that will be deal by the bot like Student Services Center (SSC).
The application tools, which are used in the development of are;
Python language
Python interpreter
NLTK
Pycharm
Tensor flow
Keras
The essential benefits are as follow i.e.
The user can get information about the admissions, how to get admission, how to know the eligibility criteria of concerning program.
The user can get information about the fee structure of degree programs.
The user can get information about the programs that are offered by the university.
The user can also get the information about the departments.
Student can input the diffrent queries and chatbot giving answer them by using the model in which we train it.
NLTk is use for processing the language and genrate the response of the pattern .
Data mining algos will be use for getting usefull patterns from the large amount of the data.
| Elapsed time in (days or weeks or month or quarter) since start of the project | Milestone | Deliverable |
|---|---|---|
| Month 1 | research about AI and design frontend | frontend design |
| Month 2 | gather data and process it | dataset |
| Month 3 | train the model and do coding | complete software |
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