AI Chatbot for Gate Trend Prediction

Abstract

-ThepreparationforGATErequiresstructured planning, conceptual clarity, and awareness of shifting trends in the emphases of the syllabus and the question patterns. A sizeable proportion of the students face problems regarding dispersed study materials, lack of faculty interaction opportunities, and identification of high-priority topics. To address such issues, this work proposes a GATE preparation AI-powered Chatbot, integrated with a syllabus-aware query answering and a Question and Syllabus Trend Prediction System. In an approach to provide relevant and accurate responses to the queries of the students, the chatbot is designed using NLP and RAG. Adding this, a machine learning-based trend prediction platform has been initiated, which can analyzethequestionpapersfrompreviousyearstodothe prediction of the the topic-level importance and the frequency of questions that might come in upcoming examinations. The sum of these features results in an intelligent and accessible learning toll which can work collaborativelywiththestudentsduringtheirstudypath. Thesystemtargetsatreducingmentalloadbyimproving the efficiency in self-study and letting the students more focus on high-value areas with backing data.