Application of AI-Researched Knowledge to the Intelligent Retrieval of Educational Materials

Abstract

Managing and organizing vast amounts of digital teaching materials has emerged as a critical concern for educators as education
informatization progresses. The teaching resource service system relies on a reliable search mechanism. An AI search engine is
a practical and dependable option for building AI search systems, and using one to search educational materials thoroughly and
effectively is a great first step. This article provides an overview of the intelligent search system, discusses its design concepts
and technical standards, explains its database design and functional architecture, and then describes the method and principles
of the search system’s implementation. This study suggests incorporating the computed feature word weights in the basic education
domain into the algorithm for computing the weights of abstract sentences. Simultaneously examining the position of
the sentence, its length, and other texts is done by analyzing the features of basic education resources and current automatic
abstracting methods. Surface statistics provide an approach for automated summarization. Additionally, this article provides an
overview of the current state of the automatic abstract system operating in the basic education resource search engine, outlines
the steps for implementing AI-based search design ideas, and looks forward to future improvement efforts.