Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102375
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorLi, Xen_US
dc.creatorZheng, Pen_US
dc.creatorBao, Jen_US
dc.creatorGao, Len_US
dc.creatorXu, Xen_US
dc.date.accessioned2023-10-18T07:51:39Z-
dc.date.available2023-10-18T07:51:39Z-
dc.identifier.issn2095-8099en_US
dc.identifier.urihttp://hdl.handle.net/10397/102375-
dc.language.isoenen_US
dc.publisherGaodeng Jiaoyu Chubansheen_US
dc.rights© 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Li, X., Zheng, P., Bao, J., Gao, L., & Xu, X. (2021). Achieving cognitive mass personalization via the self-X cognitive manufacturing network: an industrial knowledge graph-and graph embedding-enabled pathway. Engineering, 22, 14-19 is availale at https://doi.org/10.1016/j.eng.2021.08.018.en_US
dc.titleAchieving cognitive mass personalization via the Self-X cognitive manufacturing network : an industrial knowledge graph- and graph embedding-enabled pathwayen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage14en_US
dc.identifier.epage19en_US
dc.identifier.volume22en_US
dc.identifier.doi10.1016/j.eng.2021.08.018en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEngineering, Mar. 2023, v. 22, p. 14-19en_US
dcterms.isPartOfEngineeringen_US
dcterms.issued2023-03-
dc.identifier.scopus2-s2.0-85154609612-
dc.identifier.eissn2096-0026en_US
dc.description.validate202310 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Jiangsu Provincial Policy Guidance Program (Hong Kong/Macau/Taiwan Science and Technology Cooperationen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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