科技大数据知识图谱构建方法及应用研究综述

A survey on the construction methods and applications of sci-tech big data knowledge graph

以研究科学创新与演化规律为目的的科学学近年来迎来了进一步的发展,科技大数据领域知识图谱在其中发挥了重大的作用.本文将从科技大数据知识图谱构建及应用研究角度,对科学学研究过程中发挥重大推动作用的科技领域知识图谱技术进行系统、深入的综述,阐述科技大数据知识图谱构建过程中涉及的科技实体抽取、科技实体消歧、科技关系抽取、科技关系推断等问题,对科技实体推荐、科技社区发现、科技实体评价、学科交叉以及学科演化等科技大数据知识图谱分析挖掘方法进行系统梳理,并给出科技大数据知识图谱未来的研究及应用方向.

Recently,the knowledge graph(KG)of sci-tech and big data technology has played a paramount role in the development of the science of science.We carry out a systematic and in-depth review of KG construction and big data technology application in the sci-tech field.Specifically,we explain the issues of sci-tech entity extraction,sci-tech entity disambiguation,sci-tech relationship extraction,and sci-tech relationship inference involved in the construction of sci-tech big data KG,and give a systematized summary of the analysis and mining methods of the sci-tech big data KG,such as sci-tech entity recommendation,sci-tech community detection,sci-tech entity evaluation,interdisciplinary research,and disciplinary evolution analysis.Lastly,we give the future research and application directions of the sci-tech KG.