.png){kind=icon}
.png){kind=icon}
Return
Semantic methods supporting engineering design innovation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.aei.2010.08.001.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we present a metric based on semantic relatedness which operates on semantic knowledge representations of engineering design and show how it can support design innovation. Our semantic knowledge representation is composed of an ontology representing design concepts using the National Institute of Standards and Technology (NISI) functional basis formalism. We assert that the uniqueness of a design concept is directly proportional to the mean semantic distance between itself and the set of competing design concepts represented as instances within our functional basis ontology. This leads to our Semantic Relatedness Uniqueness Metric called SeRUM. SeRUM draws upon semantic functional model representations of design concepts and computer science semantic relatedness techniques. SeRUM provides design teams a measure of their effectiveness in terms of generating unique design concepts. To highlight SeRUM's application in engineering design innovation, a design innovation case study is detailed and the results are discussed. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords:
Ideation
Engineering design
Functional models
Semantic Web
Ontologies
Metrics
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.9
Papers:
4.0K
Citations:
1.7W