{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T15:00:25Z","timestamp":1773327625615,"version":"3.50.1"},"reference-count":36,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,9,15]]},"abstract":"<jats:p>Manufacturing industry is the foundation of a country\u2019s economic development and prosperity. At present, the data in manufacturing enterprises have the problems of weak correlation and high redundancy, which can be solved effectively by knowledge graph. In this paper, a method of knowledge graph construction in manufacturing domain based on knowledge enhanced word embedding model is proposed. The main contributions are as follows: (1) At the algorithmic level, this paper proposes KEWE-BERT, an end-to-end model for joint entity and relation extraction, which superimposes the token embedding and knowledge embedding output by BERT and TransR so as to improve the effect of knowledge extraction; (2) At the application level, knowledge representation model ManuOnto and dataset ManuDT are constructed based on real manufacturing scenarios, and KEWE-BERT is used to construct knowledge graph from them. The knowledge graph constructed has rich semantic relations, which can be applied in actual production environment. Other than that, KEWE-BERT can extract effective knowledge and patterns from redundant texts in the enterprise, which providing a solution for enterprise data management.<\/jats:p>","DOI":"10.3233\/jifs-210982","type":"journal-article","created":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T13:58:06Z","timestamp":1629813486000},"page":"3603-3613","source":"Crossref","is-referenced-by-count":14,"title":["Knowledge graph construction based on knowledge enhanced word embedding model in manufacturing domain"],"prefix":"10.1177","volume":"41","author":[{"given":"Jin","family":"Dong","sequence":"first","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}]},{"given":"Sen","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}]}],"member":"179","reference":[{"issue":"04","key":"10.3233\/JIFS-210982_ref1","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.eng.2019.07.015","article-title":"Human\u2013Cyber\u2013Physical Systems(HCPSs) in the Context of New-Generation Intelligent Manufacturing[J]","volume":"5","author":"Zhou","year":"2019","journal-title":"Engineering"},{"issue":"04","key":"10.3233\/JIFS-210982_ref2","doi-asserted-by":"crossref","first-page":"29","DOI":"10.15302\/J-SSCAE-2018.04.006","article-title":"Research on New-Generation Intelligent Manufacturing based on Human-Cyber-Physical Systems[J]","volume":"20","author":"Wang","year":"2018","journal-title":"Strategic Study of CAE"},{"key":"10.3233\/JIFS-210982_ref3","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.psep.2018.05.009","article-title":"Sustainable industry 4.0 framework: a systematic literature review identifying the current trends and future perspectives","volume":"117","author":"Kamble","year":"2018","journal-title":"Process Safety and Environmental Protection"},{"issue":"3","key":"10.3233\/JIFS-210982_ref4","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.1109\/COMST.2017.2691349","article-title":"Industrial internet: a survey on the enabling technologies, applications, and challenges","volume":"19","author":"Li","year":"2017","journal-title":"IEEE Communications Surveys & Tutorials"},{"key":"10.3233\/JIFS-210982_ref5","first-page":"55","article-title":"Soft computing approaches for rescheduling problems in a manufacturing industry","author":"Chedid","year":"2020","journal-title":"RAIRO - 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