数据融合研究的主题与方法趋势  

Trends of Topics and Methods in Data Fusion Research

作　　者：李杰 于倩倩[1] 王玉菊[1] Li Jie;Yu Qianqian;Wang Yuju(National Science Library,Chinese Academy of Sciences,Beijing 100190,China;Department of Information Resources Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国科学院文献情报中心,北京100090 [2]中国科学院大学经济与管理学院信息资源管理系,北京100190

出　　处：《文献与数据学报》2023年第3期26-41,共16页Journal of Library and Data

基　　金：中国科学院文献情报能力建设专项项目“研发数据组织与分析挖掘的智能技术”(项目编号:E1290002)的研究成果之一。

摘　　要：[目的/意义]数据融合是实现多源数据价值的重要途径,全面分析全球数据融合研究的整体主题格局,对当前认识和研究数据融合有重要的科技情报价值。[方法/过程]采用词频与共词分析法,对Web of Science核心数据集中16053篇数据融合研究论文的热点主题和研究方法进行了分析。[结果/结论]数据融合研究在整体上呈现了显著的增长趋势,且经过30余年的发展已经形成了核心的研究热点和数据融合方法。在研究中,传感器(包括无线传感器)数据融合是该领域的研究热点方向。故障诊断、遥感、安全以及智能电网等是数据融合应用的热点场景。卡尔曼滤波法、神经网络、Dempster-Shafer证据理论以及机器学习(包括深度学习、支持向量机等)等是数据融合的热点方法,且数据融合研究中已经形成了多方法共现协同网络。[Purpose/significance]Data fusion is an important way to realize multi-source data value.Comprehensive analysis of the overall topics of global data fusion research has an important scientific and technological information value for the current data fusion research.[Method/process]The hot topics and research methods of 16053 literatures from Web of Science core collections were analyzed by word-frequency and co-word analysis.[Result/conclusion]The data fusion research has shown a significant growth trend,and after more than 30 years development,core research hotspots and methods of data fusion have been formed.In the research,the data fusion of sensors(including wireless sensors)is the core research direction in this field.Fault diagnosis,remote sensing,security and smart grid are the hotspots of the data fusion scenario.Kalman Filter,Neural Network,Dempster-Shafer Evidence Theory and Machine Learning(including Deep Learning,Support Vector Machine,etc.)are the main methods in data fusion,and the synergy network of methods have been formed in data fusion.

关 键 词：数据融合 信息融合 知识融合 多源数据集成 共词分析 VOSviewer 

分 类 号：G202[文化科学—传播学]