摘要
为满足新形势下技术趋势分析的发展要求,打破跨专业壁垒,整合多领域科研资源,构建了知识驱动的领域技术洞察与趋势分析平台Analysis。基于高效的图神经网络等资源获取方法,平台可以提高多源、多类型和海量复杂科研数据的关联处理和预测分析能力,评估和预测对科技发展具有引领作用的前沿科学和工程技术;还可以全自动分析领域技术的发展趋势,帮助科研工作者以及其他行业决策者快速定位领域技术的研究热点,提供技术发展的潜在前景和路径。
In order to meet the development requirements of technical trend analysis under the new situation, break cross-domain professional barriers, and integrate multi-domain scientific research resources, this paper constructs a knowledge-driven insight and trend analysis platform Analysis. Based on efficient graph neural network and other resource acquisition methods, the platform can improve the ability of association processing and prediction analysis of multi-source, multi-type and massive complex scientific research data, and evaluate and predict the frontier science and engineering technology that have a leading role in the development of science and technology.The platform can also automatically analyze the development trend of domain technology, help scientific researchers and other industry decision makers quikly locate the research hotspots of domain technology, and provide potential prospects and paths for technological development.
作者
李亚坤
仇瑜
刘德兵
唐杰
李涓子
LI Yakun;QIU Yu;LIU Debing;TANG Jie;LI Juanzi(Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China)
出处
《实验技术与管理》
CAS
北大核心
2021年第11期5-10,38,共7页
Experimental Technology and Management
基金
国家电网有限公司总部科技项目“面向数据运营的潜在高价值工业用户智能挖掘技术研究”(5700-202055267A-0-0-00)。
关键词
领域技术
趋势分析
科研资源
domain technology
trend analysis
research resources