Different from explicit customer needs that can be identified directly by analyzing raw data from the customers, latent customer needs are often implied in the semantics of use cases underlying customer needs information. Due to difficulties in understanding semantic implications associated with use cases, typical text mining-based methods can hardly identify latent customer needs, as opposite to keywords mining for explicit customer needs. This paper proposes a two-layer model for latent customer needs elicitation through use case reasoning. The first layer emphasizes sentiment analysis, aiming to identify explicit customer needs based on the product attributes and ordinary use cases extracted from online product reviews. Fuzzy support vector machines (SVMs) are developed to build sentiment prediction models based on a list of affective lexicons. The second layer is geared toward use case analogical reasoning, to identify implicit characteristics of latent customer needs by reasoning the semantic similarities and differences analogically between the ordinary and extraordinary use cases. Case-based reasoning (CBR) is utilized to perform case retrieval and case adaptation. A case study of Kindle Fire HD 7 in. tablet is developed to illustrate the potential and feasibility of the proposed method.
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July 2015
Research-Article
Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews
Feng Zhou,
Feng Zhou
The George W. Woodruff School
of Mechanical Engineering,
e-mail: fzhou35@gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: fzhou35@gatech.edu
Search for other works by this author on:
Roger Jianxin Jiao,
Roger Jianxin Jiao
1
The George W. Woodruff School
of Mechanical Engineering,
e-mail: rjiao@gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: rjiao@gatech.edu
1Corresponding author.
Search for other works by this author on:
Julie S. Linsey
Julie S. Linsey
The George W. Woodruff School
of Mechanical Engineering,
e-mail: julie.linsey@me.gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: julie.linsey@me.gatech.edu
Search for other works by this author on:
Feng Zhou
The George W. Woodruff School
of Mechanical Engineering,
e-mail: fzhou35@gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: fzhou35@gatech.edu
Roger Jianxin Jiao
The George W. Woodruff School
of Mechanical Engineering,
e-mail: rjiao@gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: rjiao@gatech.edu
Julie S. Linsey
The George W. Woodruff School
of Mechanical Engineering,
e-mail: julie.linsey@me.gatech.edu
of Mechanical Engineering,
Georgia Institute of Technology
,801 Ferst Drive
,Atlanta
, GA 30332e-mail: julie.linsey@me.gatech.edu
1Corresponding author.
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received August 28, 2014; final manuscript received February 4, 2015; published online May 19, 2015. Assoc. Editor: Wei Chen.
J. Mech. Des. Jul 2015, 137(7): 071401 (12 pages)
Published Online: July 1, 2015
Article history
Received:
August 28, 2014
Revision Received:
February 4, 2015
Online:
May 19, 2015
Citation
Zhou, F., Jianxin Jiao, R., and Linsey, J. S. (July 1, 2015). "Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews." ASME. J. Mech. Des. July 2015; 137(7): 071401. https://doi.org/10.1115/1.4030159
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