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Artificial intelligence - Technical framework of knowledge graph
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GB/T 42131-2022
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Basic data Standard ID | GB/T 42131-2022 (GB/T42131-2022) | Description (Translated English) | Artificial intelligence - Technical framework of knowledge graph | Sector / Industry | National Standard (Recommended) | Classification of Chinese Standard | L70 | Classification of International Standard | 35.020 | Word Count Estimation | 38,330 | Date of Issue | 2022-12-30 | Date of Implementation | 2023-07-01 | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration |
GB/T 42131-2022: Artificial intelligence - Technical framework of knowledge graph---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
ICS 35.020
CCSL70
National Standards of People's Republic of China
Artificial Intelligence Knowledge Graph Technology Framework
Posted on 2022-12-30
2023-07-01 implementation
State Administration for Market Regulation
Released by the National Standardization Management Committee
table of contents
Preface III
1 Scope 1
2 Normative references 1
3 Terms and Definitions 1
4 Abbreviations 3
5 Overview 3
5.1 Conceptual Model of Knowledge Graph 3
5.2 Technical Framework of Knowledge Graph 4
6 Knowledge Graph Provider 6
6.1 Input of Knowledge Graph Supplier 6
6.2 Output of Knowledge Graph Supplier 6
6.3 The main activities of the knowledge graph provider 6
6.3.1 Activity flow 6
6.3.2 Knowledge Representation 7
6.3.3 Knowledge Modeling 9
6.3.4 Knowledge acquisition10
6.3.5 Knowledge Fusion 13
6.3.6 Knowledge Storage 14
6.3.7 Knowledge Computing 16
6.3.8 Knowledge Traceability 17
6.3.9 Knowledge Evolution 18
6.3.10 Quality Assurance 19
7 Knowledge Graph Integrator 19
7.1 The input of the knowledge map integrator 19
7.2 The output of the knowledge graph integrator 19
7.3 Main components of the knowledge graph application system 20
7.4 The main activities of the knowledge graph integrator 20
7.4.1 Activity flow 20
7.4.2 Requirements Analysis 21
7.4.3 System design 22
7.4.4 Knowledge graph integration 23
7.4.5 Development of knowledge map application system 24
7.4.6 System maintenance 25
7.4.7 Quality Assurance 26
8 Knowledge Graph Users 26
8.1 Knowledge users 26
8.1.1 Input from knowledge users 26
8.1.2 Outputs of knowledge users 27
8.1.3 Main activities 27
8.2 Knowledge maintainers 27
8.2.1 Input from knowledge maintainers 27
8.2.2 Output of knowledge maintenance 27
8.2.3 Main activities 27
8.3 Knowledge Providers 27
8.3.1 Input from knowledge providers 27
8.3.2 Outputs of knowledge providers 27
8.3.3 Main activities 27
9 Knowledge Graph Ecosystem Partners 28
9.1 Input from knowledge graph ecological partners 28
9.2 Output of knowledge graph ecological partners 28
9.3 Main activities 28
Appendix A (informative) Description of sub-roles of knowledge graph ecological partners 29
Reference 30
foreword
This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules for Standardization Documents"
drafting.
Please note that some contents of this document may refer to patents. The issuing agency of this document assumes no responsibility for identifying patents.
This document is proposed and managed by the National Information Technology Standardization Technical Committee (SAC/TC28).
This document is drafted by. China Institute of Electronic Technology Standardization, Jiangsu Saixi Technology Development Co., Ltd., Shenzhen Saixi Information Technology Co., Ltd.
Co., Ltd., Tsinghua University, Chengdu Shulian Mingpin Technology Co., Ltd., China Electronics Technology Big Data Research Institute Co., Ltd., Shenyang Neusoft Intelligent Medical Technology
Research Institute Co., Ltd., Beijing Huayu Yuandian Information Service Co., Ltd., Beijing Guoshuang Technology Co., Ltd., Qingdao Baheal Intelligent Technology Co., Ltd.
Co., Ltd., Wangzhi Tianyuan Technology Group Co., Ltd., Huawei Cloud Computing Co., Ltd., Beijing Baifendian Technology Group Co., Ltd., four
Sichuan University, Shanghai Yitu Network Technology Co., Ltd., Tencent Cloud Computing (Beijing) Co., Ltd., Tianjin University, Chinese Academy of Medical Sciences
Institute of Medical Engineering, Tongfang Knowledge Network Digital Publishing Technology Co., Ltd., Beijing Car Home Information Technology Co., Ltd., Beijing Jinghang Computing
Institute of Communications, University of South China, NSFOCUS Technology Group Co., Ltd., Hisense Group Holdings Co., Ltd., China Zheshang Bank Co., Ltd.
Division, Beijing Haizhi Xingtu Technology Co., Ltd., Zhijiang Laboratory, Nanjing Xingzheyi Intelligent Transportation Technology Co., Ltd., Shandong Province Artificial Intelligence Research
Institute, Neusoft Group Co., Ltd., Shandong Yiyun Information Technology Co., Ltd., Huawei Technologies Co., Ltd., Shandong Provincial Computing Center (National Super
Class Computing Jinan Center), Dianke Cloud (Beijing) Technology Co., Ltd., Nanjing Inspector Intelligent Technology Co., Ltd., China Telecom Corporation
Research Institute, Beijing Zhitong Yunlian Technology Co., Ltd., Xiamen Yitong Software Technology Co., Ltd., Shanghai Intelligent Manufacturing Functional Platform Co., Ltd., Shanghai
Sea Intelligent Manufacturing System Innovation Center Co., Ltd., Nanjing Keji Data Technology Co., Ltd., Nanjing University of Aeronautics and Astronautics, China Electronics Technology Group
Ma Hongkui, Yang Juan, Hu Fanghuai, Li Lun, Cao Yang, Zhang Chen, Li Linfeng.
Artificial Intelligence Knowledge Graph Technology Framework
1 Scope
This document gives the conceptual model and technical framework of the knowledge graph, and specifies the knowledge graph supplier, knowledge graph integrator, knowledge graph
Input, output, main activities, and quality general performance requirements of spectrum users and knowledge graph ecological partners.
This document is applicable to the construction, application, implementation and maintenance of knowledge graphs and their application systems.
2 Normative references
This document has no normative references.
3 Terms and Definitions
The following terms and definitions apply to this document.
3.1
knowledge knowledge
Awareness, judgment or skill acquired through study, practice or exploration.
[Source. GB/T 23703.2-2010,2.1]
3.2
Entity entity
Objects that exist independently.
3.3
entity type
An abstraction for a collection of entities with the same properties.
3.4
knowledge element
An independent unit of knowledge that does not need to be subdivided to describe a certain thing or concept.
Note. Entities, entity types (concepts), attributes, relationships, relationship types, events, rules, etc. mentioned in this document are collectively referred to as knowledge elements.
3.5
contact association
A semantic association between two or more objects.
[Source. ISO 13374-2.2007, B.2.2.4, with modifications]
3.6
Knowledge graph knowledgegraph
A collection of knowledge elements and their connections described in a structured form.
3.7
Knowledge unit knowledgeunit
A collection of knowledge elements organized according to a certain relationship.
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