TY - JOUR
T1 - A context-aware diversity-oriented knowledge recommendation approach for smart engineering solution design
AU - Li, Xinyu
AU - Chen, Chun Hsien
AU - Zheng, Pai
AU - Jiang, Zuhua
AU - Wang, Linke
N1 - Funding Information:
This work is conducted within the Delta-NTU Corporate Lab for Cyber–Physical Systems with funding support from Delta Electronics Inc and the National Research Foundation (NRF) Singapore under the Corporate Laboratory @ University Scheme (Ref. RCA-16/434 ; SCO-RP1 ) at Nanyang Technological University, Singapore. The authors also acknowledge the funding support from the National Natural Science Foundation of China (No. 71671113 ).
Publisher Copyright:
© 2021 Elsevier B.V.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3/5
Y1 - 2021/3/5
N2 - To proactively fulfill multiple stakeholders’ needs in the engineering solution design process, the knowledge recommendation approach is adopted as a key element in the knowledge management system. Nevertheless, most existing knowledge recommendation approaches cannot simultaneously meet the higher standard of in-context accuracy and diversity. To address the issue, this paper proposes a context-aware diversity-oriented knowledge recommendation approach, thereby assisting stakeholders to accomplish engineering solution design in a smarter manner. Three diversity concerns, namely item-diversity, context-diversity, and user-diversity are addressed by semantic-based content analysis, context definition and awareness, and user profile modeling, respectively. Hence, the proposed approach not only maximizes the diversity of the recommended knowledge but also guarantees its accuracy under multiple problem-solving contexts. Moreover, a practical engineering solution design case on a Smart 3D printer platform is conducted, to validate the efficacy of the proposed approach in providing usable and diverse knowledge items. It is anticipated this work can provide useful insights to practitioners in their knowledge-based engineering solution design process.
AB - To proactively fulfill multiple stakeholders’ needs in the engineering solution design process, the knowledge recommendation approach is adopted as a key element in the knowledge management system. Nevertheless, most existing knowledge recommendation approaches cannot simultaneously meet the higher standard of in-context accuracy and diversity. To address the issue, this paper proposes a context-aware diversity-oriented knowledge recommendation approach, thereby assisting stakeholders to accomplish engineering solution design in a smarter manner. Three diversity concerns, namely item-diversity, context-diversity, and user-diversity are addressed by semantic-based content analysis, context definition and awareness, and user profile modeling, respectively. Hence, the proposed approach not only maximizes the diversity of the recommended knowledge but also guarantees its accuracy under multiple problem-solving contexts. Moreover, a practical engineering solution design case on a Smart 3D printer platform is conducted, to validate the efficacy of the proposed approach in providing usable and diverse knowledge items. It is anticipated this work can provide useful insights to practitioners in their knowledge-based engineering solution design process.
KW - Context-aware
KW - Diversity
KW - Engineering knowledge
KW - Engineering solution design
KW - Knowledge recommendation
UR - http://www.scopus.com/inward/record.url?scp=85100061224&partnerID=8YFLogxK
U2 - 10.1016/j.knosys.2021.106739
DO - 10.1016/j.knosys.2021.106739
M3 - Journal article
AN - SCOPUS:85100061224
SN - 0950-7051
VL - 215
JO - Knowledge-Based Systems
JF - Knowledge-Based Systems
M1 - 106739
ER -