NDLI: Rule selection for knowledge-based product design

Content Provider	IEEE Xplore Digital Library
Author	Kyoung-Yun Kim Keunho Choi Jihoon Kim Ohbyung Kwon
Copyright Year	2010
Description	Author affiliation: Dept of Info & Decision Sys, San Diego State University, San Diego, CA (Ohbyung Kwon) \|\| Dept of Ind & Mnfg Engg, Wayne State University, Detroit, USA (Kyoung-Yun Kim; Keunho Choi; Jihoon Kim)
Abstract	Knowledge-intensive and collaborative environment becomes more significant in the modern product development. To realize a true knowledge-based product design environment, however, the complexity of design constraint is still cumbersome issue to tackle. Typically, product design information comes from various sources and rapidly changes; design is evolutionary. Thus, a minimal set of rules is required to make an appropriate design decision. This paper aims to present a rule reduct based approach to select systematically minimal set of rules. Rough set theory synthesizes approximation of concepts, analyzes data by discovering patterns, and classifies into certain decision classes, which can be extracted from data by means of methods based on Boolean reasoning and discernibility. In this paper, this rule reduct based approach is compared with the absorption theorem based approach.
Starting Page	518
Ending Page	524
File Size	181902
Page Count	7
File Format	PDF
ISBN	9781424473847
e-ISBN	9781424473861
DOI	10.1109/ICICIS.2010.5534773
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Ontologies Product design Rule reduct Design rule selection Computational complexity Knowledge-based product design Rough set theory Semantic product design Absorption Collaboration Set theory Product development Manufacturing Pattern analysis
Content Type	Text
Resource Type	Article

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