Automated mapping of product features mined from online customer reviews to engineering product characteristics

Sung Woo Kang, Conrad S. Tucker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication36th Computers and Information in Engineering Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791850084
DOIs
StatePublished - Jan 1 2016
EventASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016 - Charlotte, United States
Duration: Aug 21 2016Aug 24 2016

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume1B-2016

Other

OtherASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016
CountryUnited States
CityCharlotte
Period8/21/168/24/16

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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  • Cite this

    Kang, S. W., & Tucker, C. S. (2016). Automated mapping of product features mined from online customer reviews to engineering product characteristics. In 36th Computers and Information in Engineering Conference (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1B-2016). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2016-59772