大规模知识图谱及其应用研究

Research on Large-scale Knowledge Graph and Its Application

[目的/意义]阐述大规模知识图谱及其典型应用,分析其所面临挑战及对策,展望其发展趋势。[方法/过程]采用网络调查法、内容分析法系统梳理、阐述大规模知识图谱及其典型应用,所面临挑战及对策、发展趋势。[结果/结论]大规模知识图谱典型应用为语义搜索、深度问答、智能推荐等;面临特征知识表示、知识缺失、知识更新、功能全面性等挑战;向特色化、开放化、智能化方向发展。

[ Purpose/significance ] This paper aims to expound large-scale knowledge graph and its typical application, ana- lyze the challenges and countermeasures it faces, and present its development trend. [ Method/process] Using the methods of net- work investigation and content analysis, the paper systematically explores the large-scale knowledge graph and its typical applica- tions, its challenges and countermeasures, as well as its development trends. [ Result/conclusion ] The typical applications of large-scale knowledge graph are semantic search, in-depth question and answer, intelligent recommendation, etc. It faces the challenges of feature knowledge representation, knowledge lacking, knowledge updating, function comprehensiveness, and so on. It is developing in the direction of specialization, openness and intelligence.