Research on Big Data Retrieval System of Intelligent Computer AI in Post-Moore Era

This paper proposes a big data search platform in the post-Moore period. The algorithm can adapt to the storage and calculation of large-scale data, and can search video data quickly. The aim of this research is low accuracy and low recall rate of existing retrieval algorithms based on artificial neural networks. Cite Space technology is used to obtain the corresponding information through the statistical analysis of the keywords in the massive data. This project intends to MapReduce to analyze the correlation characteristics of massive data. The large-scale data analysis method of MapReduce is studied, so as to achieve the automatic query of massive data. And we pre-inspect it before entering the warehouse and use a variety of tools for data access and management. Simulation results show that the new method proposed in this project can effectively improve the computational performance of spatiotemporal big data, and improve its application in massive, multi-source, heterogeneous and other complex data.