Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
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Article Number | 01010 | |
Number of page(s) | 5 | |
Section | Network Security System, Neural Network and Data Information | |
DOI | https://doi.org/10.1051/matecconf/201823201010 | |
Published online | 19 November 2018 |
Design of University Library and Information Management System Based on Big Data Fusion
Huali College Guangdong University of Technology, 511325 Guangdong Guangzhou, China
In order to improve the ability of library and information management in colleges and universities, and improve intelligent retrieval level of books, a design method of library information management system is proposed based on big data fusion. The phase space reconstruction technology is used to reconstruct the feature of library and information. The feature quantity of semantic concept set of library information is extracted, and the classification storage and information retrieval of library information is carried out by fuzzy clustering method. The adaptive training method is used for feature fusion, and big data fusion of library and information is realized in high dimensional feature space. The data processing center is set up under the Linux kernel environment, the application program of the university library information management system is developed under the Linux kernel, and the VXI bus technology is used to transmit and schedule the university library information management information and data. Realize the software development and design of the school library information management system. The test results show that the design of university library information management system with this method has good information storage and scheduling ability, and it improves the performance of library information retrieval. In the information recall rate and recall rate and other indicators performance has an advantage.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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