Integration and optimization of ancient literature information resources based on big data technology

Abstract

Big data refers to a collection of data that cannot be captured, managed, and processed with conventional software tools within a certain time frame. It is a massive, high-volume, high-volume data that requires new processing models to have stronger decision-making power, insight and discovery, process optimization capabilities, growth rate, and diversified information assets. This article aims to study the integration and optimization of ancient literature information resources of big data technology, that is, to integrate and optimize ancient literature information resources through big data technology and make the literature more systematic and complete, allowing readers to find and browse literature more conveniently. This paper focuses on the literary works and the related collation, annotation, and textual research results and divides the scope of each subtopic according to the genre. The biggest difference between the information platform built in this paper and the existing ancient books database is that it has the functions of semantic analysis, subject retrieval, data generation, and so on. After text learning, the computer can automatically classify related vocabulary. Based on the effective integration of big data and cultural resources, the experimental results of this article show that, so far, through technical optimization and resource integration, the number of ancient literature reincorporated has exceeded 12,000 copies, and more than 10,000 publications have been restored. Therefore, big data technology is essential for the integration and optimization of cultural resources.