%A Zhiqiang Wu,Zhongming Zhu,Wei Liu,Sili Wang %T Research and Practice on the Extension of Knowledge Analysis and Visualization Function in CSpace %0 Journal Article %D 2019 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2018.0903 %P 112-119 %V 3 %N 3 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4623.shtml} %8 2019-03-25 %X

[Objective] This paper aims to expand the function of knowledge analysis and visualization in CSpace, and realize the full integration of knowledge analysis and visualization services into the user’s knowledge utilization and knowledge innovation process. [Context] The function of knowledge analysis and visualization is an important development direction of institutional repository research and construction. Expanding their functions could provide users with better quality knowledge services in the process of knowledge dissemination and utilization. [Methods] First, we rebuilt the knowledge analysis and visualization functional framework. Then, we upgraded Solr index and optimized the associated storage structure of knowledge based on Solr sub document. We designed and implemented organization data, project data, journal data specification and management functions, used Echarts to build a modular, flexible embedded visualization tool set, improved the basic service capabilities of knowledge analysis and visualization. Finally, we optimized and reconstructed the function of knowledge analysis and visualization based on user’s knowledge application requirements. [Results] The extension of knowledge analysis and visualization function which can provide with more fine-grained knowledge analysis, flexible customization, ubiquitous map visualization and export functions in CSpace is realized, and deployed and applied in more than 30 scientific research institutions and universities. Limited by the data normative problem, the developed subject analysis function has not been put into practical use. [Conclusions] The ability building for knowledge analysis and visualization based on user needs enhance knowledge service attribute in institutional repository, and can effectively promote knowledge utilization and knowledge innovation.