Development and Prospect of Big Data Knowledge Engineering

Big Data Knowledge Engineering is the infrastructure of artificial intelligence, a common requirement faced by various industries and fields, and the inevitable path for the digitalization to intelligence. In this paper, we firstly elaborate on the background and connotation of big data knowledge en...

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Những tác giả chính: Zheng Qinghua, Liu Huan, Gong Tieliang, Zhang Lingling, Liu Jun
Định dạng: Bài viết
Ngôn ngữ:zho
Được phát hành: 《中国工程科学》杂志社 2023-04-01
Loạt:中国工程科学
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Truy cập trực tuyến:http://www.engineering.org.cn/en/10.15302/J-SSCAE-2023.02.018
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author Zheng Qinghua
Liu Huan
Gong Tieliang
Zhang Lingling
Liu Jun
author_facet Zheng Qinghua
Liu Huan
Gong Tieliang
Zhang Lingling
Liu Jun
author_sort Zheng Qinghua
collection DOAJ
description Big Data Knowledge Engineering is the infrastructure of artificial intelligence, a common requirement faced by various industries and fields, and the inevitable path for the digitalization to intelligence. In this paper, we firstly elaborate on the background and connotation of big data knowledge engineering and propose a research framework of “data knowledgeization, knowledge systematization, and knowledge reasoning”. Secondly, we sort out the key technologies of knowledge acquisition and fusion, knowledge representation, and knowledge reasoning and introduce engineering applications in typical scenarios such as smart education, tax risk control, and smart healthcare. Thirdly, we summary the challenges faced by big data knowledge engineering and predict the future research directions including complex big data knowledge acquisition, knowledge+data hybrid learning, and brain-inspired knowledge coding and memorizing. Finally, several suggestions are given by the research: guiding interdisciplinary integration and establishing major and key R&D projects to promote the basic theory and technological breakthroughs of big data knowledge engineering; strengthening communication and cooperation between enterprises and research institutions as well as promoting cutting-edge research results to form application demonstrations, so as to establish an industry-standard system for big data knowledge engineering; exploring school-enterprise cooperation in line with market demands, orienting towards major application needs, and accelerating the landing application of big data knowledge engineering technology in the country's important industries.
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spelling doaj.art-44041f55550b4b22a0ce00003992c6822023-11-14T11:27:34Zzho《中国工程科学》杂志社中国工程科学2096-00342023-04-0125220822010.15302/J-SSCAE-2023.02.018Development and Prospect of Big Data Knowledge EngineeringZheng Qinghua0 Liu Huan 1 Gong Tieliang 2 Zhang Lingling 3 Liu Jun4 Xi‘an Jiaotong University, Xi‘an 710049, China School of Computer Science and Technology, Xi‘an Jiaotong University, Xi‘an 710049, China ; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering, Xi‘an 710049, China School of Computer Science and Technology, Xi‘an Jiaotong University, Xi‘an 710049, China School of Computer Science and Technology, Xi‘an Jiaotong University, Xi‘an 710049, China School of Computer Science and Technology, Xi‘an Jiaotong University, Xi‘an 710049, China ; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering, Xi‘an 710049, China Big Data Knowledge Engineering is the infrastructure of artificial intelligence, a common requirement faced by various industries and fields, and the inevitable path for the digitalization to intelligence. In this paper, we firstly elaborate on the background and connotation of big data knowledge engineering and propose a research framework of “data knowledgeization, knowledge systematization, and knowledge reasoning”. Secondly, we sort out the key technologies of knowledge acquisition and fusion, knowledge representation, and knowledge reasoning and introduce engineering applications in typical scenarios such as smart education, tax risk control, and smart healthcare. Thirdly, we summary the challenges faced by big data knowledge engineering and predict the future research directions including complex big data knowledge acquisition, knowledge+data hybrid learning, and brain-inspired knowledge coding and memorizing. Finally, several suggestions are given by the research: guiding interdisciplinary integration and establishing major and key R&D projects to promote the basic theory and technological breakthroughs of big data knowledge engineering; strengthening communication and cooperation between enterprises and research institutions as well as promoting cutting-edge research results to form application demonstrations, so as to establish an industry-standard system for big data knowledge engineering; exploring school-enterprise cooperation in line with market demands, orienting towards major application needs, and accelerating the landing application of big data knowledge engineering technology in the country's important industries. http://www.engineering.org.cn/en/10.15302/J-SSCAE-2023.02.018Big Data Knowledge Engineering, Knowledge Acquisition, Knowledge Fusion, Knowledge Representation, Knowledge Reasoning
spellingShingle Zheng Qinghua
Liu Huan
Gong Tieliang
Zhang Lingling
Liu Jun
Development and Prospect of Big Data Knowledge Engineering
中国工程科学
Big Data Knowledge Engineering, Knowledge Acquisition, Knowledge Fusion, Knowledge Representation, Knowledge Reasoning
title Development and Prospect of Big Data Knowledge Engineering
title_full Development and Prospect of Big Data Knowledge Engineering
title_fullStr Development and Prospect of Big Data Knowledge Engineering
title_full_unstemmed Development and Prospect of Big Data Knowledge Engineering
title_short Development and Prospect of Big Data Knowledge Engineering
title_sort development and prospect of big data knowledge engineering
topic Big Data Knowledge Engineering, Knowledge Acquisition, Knowledge Fusion, Knowledge Representation, Knowledge Reasoning
url http://www.engineering.org.cn/en/10.15302/J-SSCAE-2023.02.018
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AT liuhuan developmentandprospectofbigdataknowledgeengineering
AT gongtieliang developmentandprospectofbigdataknowledgeengineering
AT zhanglingling developmentandprospectofbigdataknowledgeengineering
AT liujun developmentandprospectofbigdataknowledgeengineering