电信运营商知识图谱技术体系研究及应用实践

doi:10.11959/j.issn.1000-0801.2022145

Abstract

Abstract:

Knowledge graph plays an important role in knowledge search, work order processing, intelligent service, fault analysis and other fields of China Mobile business and maintenance scenario.The knowledge graph technology system of China Mobile was systematically studied.Based on application scenarios and service objects, it can be divided into question ＆amp; answer retrieval knowledge graph, work-order analysis knowledge graph, system operation and maintenance knowledge graph and business operation knowledge graph.The technical architecture, business architecture and construction methods were introduced, and the planning goal of the evolution and development of knowledge graph was ultimately leaded.

Key words: knowledge graph, cognitive network, intelligence question and answer, information retrieval, intelligent operation and maintenance

CLC Number:

TP391.1

Dongming ZHAO. Research and application practice of knowledge graph technology system for telecom-operators[J]. Telecommunications Science, 2022, 38(8): 151-162.

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References 15

[1]	PAN J Z , EDELSTEIN E , BANSKY P ,et al. A knowledge graph based approach to social science surveys[J]. Data Intelligence, 2021,3(4): 477-506.
[2]	HUANG X Q , TANG J Y , TAN Z ,et al. Knowledge graph embedding by relational and entity rotation[J]. Knowledge-Based Systems, 2021(229): 107310.
[3]	ZHENG W B , YAN L , GOU C ,et al. Pay attention to doctor-patient dialogues:Multi-modal knowledge graph attention image-text embedding for COVID-19 diagnosis[J]. Information Fusion, 2021(75): 168-185.
[4]	TOSI M D L , DOS REIS J C . SciKGraph:a knowledge graph approach to structure a scientific field[J]. Journal of Informetrics, 2021,15(1): 101109.
[5]	WANG Z K , LI L J , ZENG D ,et al. Incorporating prior knowledge from counterfactuals into knowledge graph reasoning[J]. Knowledge-Based Systems, 2021(223): 107035.
[6]	SHA X , SUN Z , ZHANG J . Hierarchical attentive knowledge graph embedding for personalized recommendation[J]. Electronic Commerce Research and Applications, 2021(48): 101071.
[7]	LIN Q K , ZHU Y F , LU H ,et al. Improving university faculty evaluations via multi-view knowledge graph[J]. Future Generation Computer Systems, 2021(117): 181-192.
[8]	ABU-SALIH B , AL-TAWIL M ,, ALJARAH I ,et al. Relational learning analysis of social politics using knowledge graph embedding[J]. Data Mining and Knowledge Discovery, 2021,35(4): 1497-1536.
[9]	BUCHGEHER G , GABAUER D , MARTINEZ-GIL J , ,et al. Knowledge graphs in manufacturing and production:a systematic literature review[J]. IEEE Access, 2020: 55537-55554.
[10]	XUE Y Y , JIN J H , SONG A B ,et al. Relation-based multi-type aware knowledge graph embedding[J]. Neurocomputing, 2021(456): 11-22.
[11]	NIU H R , HE H T , FENG J Z ,et al. Knowledge graph completion based on GCN of multi-information fusion and high- dimensional structure analysis weight[J]. Chinese Journal of Electronics, 2022,31(2): 387-396.
[12]	DANG F R , TANG J T , PANG K Y ,et al. Constructing an educational knowledge graph with concepts linked to Wikipedia[J]. Journal of Computer Science and Technology, 2021,36(5): 1200-1211.
[13]	WANG W G , XU Y L , DU C H ,et al. Data set and evaluation of automated construction of financial knowledge graph[J]. Data Intelligence, 2021,3(3): 418-443.
[14]	CHEN Y . Constructing bug knowledge graph as a service for bug search[J]. International Journal of Software Engineering and Knowledge Engineering, 2021,31(1): 81-98.
[15]	PU F , ZHANG Z , FENG Y ,et al. Learning context-based embeddings for knowledge graph completion[J]. Journal of data and Information Science, 2022,7(2): 23-29.

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