摘要
随着5G技术的日趋成熟,运营商相关研究人员面临着快速掌握5G相关知识的压力,然而5G知识内容种类繁多,知识面广,如何高效地从5G协议中查询到亟需学习的知识点是当前亟待解决的问题,为了解决这一问题,本文基于知识图谱及信息搜索方法构建5G协议知识库。由于网优人员搜索相关知识一般只需得到与关键字相关的知识信息,而不必通晓全文,本文采用专业领域知识库结合多种方法对信息进行抽取,建立术语的属性、基本关系以及文本结构的关系,同时采用Neo4j图数据库对构建成的三元组进行存储,极大地提高了搜索性能,本文将该知识图谱运用到5G协议知识智能检索中,并取得了很好的效果。
With the maturity of 5G technology, operator-related researchers face the pressure to quickly acquire 5G knowledge. However, there are various types of 5G knowledge content with a wide range, and how to efficiently extract the knowledge points from 5G protocol is an urgent issue to be solved. In order to solve it, this paper constructs a 5G protocol knowledge base using the methods of knowledge graph and information search. Since network optimization engineers usually need to get knowledge related to key words rather than being familiar with the full text when searching relevant knowledge, this paper adopts professional domain knowledge bases and combines multiple methods to extract information to establish term attributes, basic relationships and text structures. At the same time, the paper also uses the Neo4j graph database to store the construed triples, which greatly improves the search performance. This paper applies the knowledge graph to intelligent retrieval in 5G protocol knowledge and obtains a successful achievement.
作者
徐健
Xu Jian(Wireless Network Optimization Center China Mobile Communications Group Fujian Co.,Ltd.,Fuzhou 350001,China)
出处
《移动通信》
2020年第8期73-79,共7页
Mobile Communications
作者简介
徐健(orcid.org/0000-0002-8022-0382):硕士毕业于北京邮电大学,现任职于中国移动通信集团福建有限公司网络部无线优化中心,主要研究方向为新技术在无线网络优化领域的应用。
