In this section
@article{Zuo:2022:10.3390/jintelligence10040103,
author = {Zuo, H and Jing, Q and Song, T and Sun, L and Childs, P and Chen, L},
doi = {10.3390/jintelligence10040103},
journal = {Journal of Intelligence},
title = {WikiLink: an encyclopedia-based semantic network for design creativity},
url = {http://dx.doi.org/10.3390/jintelligence10040103},
volume = {10},
year = {2022}
}
TY - JOUR
AB - Data-driven design is a process to reuse data sources and provide valuable information to provoke creative ideas in the stages of design. However, existing semantic networks for design creativity are built on data sources restricted to technological and scientific information. Existing studies build the edges of a semantic network on statistical or semantic relationships, which are less likely to make full use of the benefits from both types of relationships and discover implicit knowledge for design creativity. Therefore, to overcome the gaps, we constructed WikiLink, a semantic network based on Wikipedia, which is an integrated source of general knowledge and specific knowledge, with broad coverage of disciplines. The weight in WikiLink fuses both the statistic and semantic weights between concepts instead of simply one type of weight, and four algorithms are developed for inspiring new ideas. Evaluation experiments are undertaken, and the results show that the network is characterised by high coverage of terms, relationships and disciplines, which demonstrates and supports the network’s effectiveness and usefulness. A demonstration and case study results indicate that WikiLink can serve as an idea generation tool for creativity in conceptual design. The source code of WikiLink and the backend data are provided open-source for more users to explore and develop.
AU - Zuo,H
AU - Jing,Q
AU - Song,T
AU - Sun,L
AU - Childs,P
AU - Chen,L
DO - 10.3390/jintelligence10040103
PY - 2022///
SN - 2079-3200
TI - WikiLink: an encyclopedia-based semantic network for design creativity
T2 - Journal of Intelligence
UR - http://dx.doi.org/10.3390/jintelligence10040103
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000902416800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR - https://www.mdpi.com/2079-3200/10/4/103
UR - http://hdl.handle.net/10044/1/112607
VL - 10
ER -
Dyson School of Design Engineering
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