The knowledge of education policy will bring an array of new growth, but it has necessitated an improved type of human–machine intercommunica-tion, in which the machine enhances a thoughtful and interactive intelligence. Natural language processing (NLP), a part of artificial intelligence (AI), is the competence of a computer program to comprehend spoken and written human language (https://www.linguamatics.com/what-text-mining-text-analytics-and-natural-language-processing; Zhang and Segall in IJITDM 7(4):683–720, (2008)) [1, 2]. After being thoughtful about it, in mining, one should have sagacity for the predetermination of policy (Bhardwaj in Int J Eng Res Technol (IJERT) 1(3), 2012; Maes in Commun ACM 7:30–40, 1994) [3, 4]. Using NLP, this provides a quick way of extracting information about education policy. This paper focuses on manipulating NLP commands after data collection using unstructured interviews about the attitude of NLP and then filling out a website questionnaire form to collect the satisfaction result. Coding is executed to get the required data using Python and NLP. During the analysis of feedback at colleges in Jaipur, Rajasthan, it is divulged about the satisfaction of using NLP commands, so it is observed that NLP creates a convenient way of mining. The goal behind this text mining is to identify the importance of NLPs in getting data into an integrated form. Lastly, in the execution phase, it narrates the process to obtain cognition for extricating data about policies for gratification.

P. Jain envelope symbolenvelope symbolenvelope symbol · S. Lal Jayoti Vidyapeeth Women’s University, Jaipur, Rajasthan, India e-mail: Pooja1981jain@yahoo.com

S. Lal e-mail: dean.fet@jvwu.ac.in

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Mishra et al. (eds.), Advances in IoT and Security with Computational Intelligence, Lecture Notes in Networks and Systems 756, https://doi.org/10.1007/978-981-99-5088-1_14

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