Abstract: In order to improve the ability of searching and identifying information in natural resources data, this paper puts forward a method of searching information in natural resources data based on hash algorithm. Through the data center technology, the problems of information source positioning, data directory organization, data semantic definition and expression, and data entity relationship construction in natural resource data center are solved. Combined with the distribution of resource data stream, the information structure reorganization and data encryption in natural resource data center are realized by using hash algorithm, and the parameters of information quality control model in natural resource data center are established. Through natural resource data governance and semantic reconstruction, the characteristics detection and redundancy arrangement of information data in natural resource data center are realized by standardizing data collection rules, and they are stored in the intermediate database. Through data governance rules, the information in the natural resources data is structured and managed, and stored in the publishing library. Through all kinds of data processing tools, all kinds of data are processed, cleaned and reconstructed, and through Hash algorithm and data aggregation processing, information detection in natural resources data is realized. The simulation results show that the precision rate of natural resource data retrieval by this method is high.

Qian Li, “Information Retrieval Method of Natural Resources Data based on Hash Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 14(3), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01403108

@article{Li2023,
title = {Information Retrieval Method of Natural Resources Data based on Hash Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01403108},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01403108},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {3},
author = {Qian Li}
}