Construction Methods of Knowledge Mapping for Full Service Power Data Semantic Search System

被引:2
作者
Chen, Tong [1 ]
Zhang, Shujuan [2 ]
Wang, Yuan [3 ]
Chen, Zhengbo [1 ]
Jing, Wenfeng [4 ]
机构
[1] State Grid Zhejiang Power Co Ltd, 8 Huanglong Rd, Hangzhou 310007, Peoples R China
[2] State Grid Anhui Power Co Ltd, 33 Xinjian St, Xuancheng 242100, Langxi County, Peoples R China
[3] NARI Grp Co Ltd, 19 Chengxin Ave, Nanjing 211000, Peoples R China
[4] Xi An Jiao Tong Univ, Sch Math & Stat, 28 Xianning West Rd, Xian 710049, Shaanxi, Peoples R China
来源
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY | 2021年 / 93卷 / 2-3期
关键词
Power dispatch; Fault recovery; Semantic web; Semantic search; Knowledge mapping;
D O I
10.1007/s11265-020-01591-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The power sector continues to accumulate a large amount of data resources, including relevant standard specifications, technical documents, management documents, fault resolution records. How to quickly query and intelligently search these documents is of great value for grid dispatching and fault recovery. The domain search system of traditional power grid is based on keywords, and has the problems of low precision and recall rate. It cannot understand the business language and cannot support semantic reasoning. This paper designs and implements a method based on knowledge mapping to construct the power domain semantic search system. Semantic knowledge extraction of unstructured data is carried out by intelligent domain segmentation technology, organized and stored as knowledge mapping, and semantic search for support reasoning is realized based on knowledge mapping. The process of constructing domain semantic search system is introduced. Experiments show that the accuracy rate and recall rate of the method have been greatly improved.
引用
收藏
页码:275 / 284
页数:10
相关论文
共 14 条
[1]   Comparison of semantic-based local search methods for multiobjective genetic programming [J].
Dou, Tiantian ;
Rockett, Peter .
GENETIC PROGRAMMING AND EVOLVABLE MACHINES, 2018, 19 (04) :535-563
[2]   Semantic-Aware Searching Over Encrypted Data for Cloud Computing [J].
Fu, Zhangjie ;
Xia, Lili ;
Sun, Xingming ;
Liu, Alex X. ;
Xie, Guowu .
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2018, 13 (09) :2359-2371
[3]   Neurally-Guided Semantic Navigation in Knowledge Graph [J].
He, Liang ;
Shao, Bin ;
Xiao, Yanghua ;
Li, Yatao ;
Liu, Tie-Yan ;
Chen, Enhong ;
Xia, Huanhuan .
IEEE TRANSACTIONS ON BIG DATA, 2022, 8 (03) :607-615
[4]  
Jian C, 2017, COMPUTER ENG APPL, V62, P36
[5]   Developing a similarity searching module for patient safety event reporting system using semantic similarity measures [J].
Kang, Hong ;
Gong, Yang .
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2017, 17
[6]   Knowledge Graphs for Social Good: An Entity-Centric Search Engine for the Human Trafficking Domain [J].
Kejriwal, Mayank ;
Szekely, Pedro .
IEEE TRANSACTIONS ON BIG DATA, 2022, 8 (03) :592-606
[7]   Multi-goal Pathfinding in Cyber-Physical-Social Environments: Multi-layer Search over a Semantic Knowledge Graph [J].
Kem, Oudom ;
Balbo, Flavien ;
Zimmermann, Antoine ;
Nagellen, Pierre .
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS, 2017, 112 :741-750
[8]   Semantic weldability prediction with RSW quality dataset and knowledge construction [J].
Kim, Kyoung-Yun ;
Ahmed, Fahim .
ADVANCED ENGINEERING INFORMATICS, 2018, 38 :41-53
[9]  
Laporte MA, 2014, LECT N BIOINFORMAT, V8574, P50
[10]   Efficient indexing for semantic search [J].
Lashkari, Fatemeh ;
Ensan, Faezeh ;
Bagheri, Ebrahim ;
Ghorbani, Ali A. .
EXPERT SYSTEMS WITH APPLICATIONS, 2017, 73 :92-114