Методи обробки даних анкетування за допомогою штучного інтелекту

Abstract

The aim of this paper is to develop an automated questionnaire processing system using AI/ML for fast data classification and filtering. Algorithms (Random Forest, SVM, NLP) are used to identify useful answers and filter out “noise” answers (20-30%). Implemented in Python (Scikit-learn, NLTK), which reduces processing time from 40 hours to 5 hours per month and increases the accuracy of analysis by 50%. Result: An effective tool for universities that automatically sorts questionnaires, saving only relevant data for further analysis.