The Information Management and Service of Open Scientific Data for University Library in the Big Data Era

Author(s):  
Yi Zhuang
2018 ◽  
Vol 232 ◽  
pp. 01010
Author(s):  
Jia Zhang

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hui Wang ◽  
Ning Wang ◽  
MeiJie Li ◽  
Simeng Mi ◽  
YaYa Shi

Health is considered an important foundation for students’ success. However, with the accelerated pace of life, rising pressure from various parties, weak health awareness, lack of exercise time, and other reasons, students’ physical quality is generally declining, the incidence of health diseases is increasing, and the onset age tends to be younger. With the development of the concept of “health first,” health management continues to expand and extend and students’ health management has attracted more attention from many aspects. Due to the late and low starting point of health management research and the lack of professional theoretical support, a complete, mature, and effective health management service system has not been established to deal with the students’ health. In order to make student health management more scientific, normative, and effective, this article has proposed big data technology to build the student health information management model. The first step of the approach is to store and analyze the data of students’ physical health. It is necessary to combine the data collection, supervision, data analysis, and data application of students’ physical health and gradually improve the national monitoring and evaluation system of students’ physical health. Student health check-up management platform is mainly used in realizing the school student information management and student health information relationship between system, science, standardization, and automation, and its main task is to use a computer to perform daily management of all previous medical information of students, such as query, modify, add, delete, and enhance the physical health of students information management ability given the large data analysis of useful information. In addition, we have built a doctor recommendation model based on online questions and answers to give specific health recommendations for students of different physiques.


Author(s):  
Qin Wu ◽  
Hui Wu

The mining and application of big data in academic journals can accelerate the construction of data journals, enhance journal’s influence, and promote the sharing and dissemination of scientific data in academic journals worldwide. This paper uses bibliometric method to retrieve published articles with the theme of big data and journal in CNKI database, analyzes the academic achievements of the development of academic journals with the application of big data in the recent five years using quantitative visualization analysis, expounds the research progress of academic journals in big data field, and discusses the advantages of big data application in periodical industry. The results show that: study on the application of big data in academic journals are gradually deepening and scientific, and the relevant research still needs more financial fund from the state and social units, big data has prominent advantages such as accuracy, scientificity and value maximization in the workflows of academic journals. The mining and application of massive data is very important for promoting the development of high-quality academic journals and optimizing the supply-demand relationship of knowledge services of academic journals.


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