TY - GEN
T1 - Automated mapping of product features mined from online customer reviews to engineering product characteristics
AU - Kang, Sung Woo
AU - Tucker, Conrad S.
N1 - Publisher Copyright:
Copyright © 2016 by ASME.
PY - 2016
Y1 - 2016
N2 - Until now, translating product features expressed in the market into quantifiable engineering metrics has primarily been a manual process. This manual process establishes product features fromlarge-scale customer feedback using a product's components from large-scale design specifications. This process exacerbates the complexity and sheer amount of information that designersmust handle during the early stages of new product development.The methodology proposed in this paper automatically identifies product features by mapping terms that describe product features from technical descriptions and customer reviews. In order to discover terms related to the features expressed in the market, the authors of this work employ WordNet and the PageRank algorithm, which search for semantically similar terms in products' technical descriptions. A case study demonstrates the methodology's viability formatching product features that are extracted from online customer reviews to the technical descriptions that address them.
AB - Until now, translating product features expressed in the market into quantifiable engineering metrics has primarily been a manual process. This manual process establishes product features fromlarge-scale customer feedback using a product's components from large-scale design specifications. This process exacerbates the complexity and sheer amount of information that designersmust handle during the early stages of new product development.The methodology proposed in this paper automatically identifies product features by mapping terms that describe product features from technical descriptions and customer reviews. In order to discover terms related to the features expressed in the market, the authors of this work employ WordNet and the PageRank algorithm, which search for semantically similar terms in products' technical descriptions. A case study demonstrates the methodology's viability formatching product features that are extracted from online customer reviews to the technical descriptions that address them.
UR - http://www.scopus.com/inward/record.url?scp=85007560292&partnerID=8YFLogxK
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U2 - 10.1115/DETC2016-59772
DO - 10.1115/DETC2016-59772
M3 - Conference contribution
AN - SCOPUS:85007560292
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 36th Computers and Information in Engineering Conference
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016
Y2 - 21 August 2016 through 24 August 2016
ER -