Applications of academic big data in the process of science and technology management

Ying LIANG; Wei ZHANG; Zhidong YU; Hongzhou SHI

doi:10.11959/j.issn.2096-0271.2019037

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Applications of academic big data in the process of science and technology management

TOPIC：ACADEMIC BIG DATA | 更新时间：2024-06-03

- Applications of academic big data in the process of science and technology management
- Big Data Research Vol. 5, Issue 5, Pages: 2019037-1(2019)
- 作者机构：
  
  1. 中国科学院计算技术研究所，北京 100190
  2. 中国科学院大学，北京 100190
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2019037
  CLC： TP315
- Online First：2019-09，
  
  Published：15 September 2019
- 稿件说明：
移动端阅览
Ying LIANG, Wei ZHANG, Zhidong YU, et al. Applications of academic big data in the process of science and technology management[J]. Big Data Research, 2019, 5(5): 2019037-1.
DOI：

Ying LIANG, Wei ZHANG, Zhidong YU, et al. Applications of academic big data in the process of science and technology management[J]. Big Data Research, 2019, 5(5): 2019037-1. DOI： 10.11959/j.issn.2096-0271.2019037.

摘要

学术大数据逐步成为提升科技管理水平的重要数据基础。通过调研国内外科技管理信息化的发展现状和特点，总结了学术大数据的发展及应用，分析了学术大数据在科技管理过程应用中面临的问题。结合我国科技管理的应用需求，设计了基于学术大数据的科技管理应用框架。基于知识图谱的学者画像构建技术和基于网络表示学习的相似作者推荐技术，利用多源异构的学术大数据，进行科研布局和资源统筹辅助决策以及科技管理过程中的专家精准推荐和成果评估评价，为提高科技管理效率提供了有效的技术支撑。

Abstract

Academic big data is gradually recognized as an important data foundation for improving the level of science and technology management.Status quo and characteristics of science and technology management informationization were investigated at home and abroad

the development and applications of academic big data were summarized

and the problems were analyzed in applications of academic big data in the process of science and technology management.The needs of science and technology management application were combined

a technology management application framework based on academic big data was designed

scholarly image construction based on knowledge graph and similar author recommendation technology based on network representation learning were applied to assist in improving the overall layout of scientific research and resources utilizing multi-heterogeneous academic big data collection.Effective technical support for improving the efficiency of science and technology management was provided.

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references

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