计算机科学
图形
知识图
模式(遗传算法)
领域知识
人工智能
情报检索
理论计算机科学
作者
Yike Wu,Yingdi Zhu,Jingchen Li,Chengye Zhang,Tianling Gong,Xiyuan Du,Tianxing Wu
出处
期刊:Communications in computer and information science
日期:2022-01-01
卷期号:: 151-159
被引量:1
标识
DOI:10.1007/978-981-19-0713-5_17
摘要
Unmanned aerial vehicles are becoming more and more important in the military field. In recent years, global hot spot military events and local conflicts have fully proved its military value. Since knowledge graph is the information basis of intelligence, how to build a high-quality unmanned aerial vehicle knowledge graph is the focus of this paper. In this work, we propose an effective method to construct a knowledge graph from textual data. We first build the schema manually based on our domain knowledge. We then extract RDF triples with SpERT. Third, we disambiguate the instance by string comparison. Finally, We import the knowledge graph into neo4j for visualization. Our team takes part in the No. 10 evaluation task (i.e., military domain-specific knowledge graph construction for military unmanned aerial vehicles) in CCKS 2021. There are two stages in this evaluation, and our approach achieves the second place in the first stage, i.e., knowledge graph quality evaluation and the third place in the second stage, i.e., knowledge graph usage evaluation.
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