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A study on warning/detection degree of warranty claims data using natural network learning

Citation

Lee, SH and Seo, SC and Yeom, SJ and Moon, K and Kang, MS and Kim, BG, A study on warning/detection degree of warranty claims data using natural network learning, Proceedings from the Sixth International Conference on Advanced Language Processing and Web Information Technology, 22-24 August, Henan, China, pp. 492-497. ISBN 9780769529301 (2007) [Refereed Conference Paper]

Copyright Statement

Copyright 2007 IEEE

DOI: doi:10.1109/ALPIT.2007.82

Abstract

Warranty service is getting important since it is an agreement between manufacturers and consumers. An issue is to find out a lower level of agreement from the perspective of manufacturers and consumers. Thus, it is very important to determine early warning/detection degree of defected parts through warranty claims data. However, there are qualitative factors more than quantitative ones in the determination. The study thus provides a part-significance knowledge extraction method based on analytic hierarchy process analysis which is appropriate to analyze those qualitative factors as well as a process to extract a list of defected parts using neural network learning.

Item Details

Item Type:Refereed Conference Paper
Keywords:warranty claims data, reliability, neural network
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Software Packages (excl. Computer Games)
Author:Yeom, SJ (Dr Soonja Yeom)
ID Code:123784
Year Published:2007
Web of Science® Times Cited:2
Deposited By:Information and Communication Technology
Deposited On:2018-01-29
Last Modified:2018-03-29
Downloads:0

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