Analysis of customer reviews for product service system design based on cloud computing

Diandi Chen; Dawen Zhang; Fei Tao; Ang Liu

doi:10.1016/j.procir.2019.03.116

Analysis of customer reviews for product service system design based on cloud computing

Diandi Chen
, Dawen Zhang
, Fei Tao
, Ang Liu^*

^*Corresponding author for this work

International Institute for Interdisciplinary and Frontiers

Beijing University of Posts and Telecommunications
University of New South Wales

Research output: Contribution to journal › Conference article › peer-review

16 Scopus citations

Abstract

Designing a product service system begins with understanding customer voices. Compared to the traditional methods such as survey, interview, customer review represents a particular kind of big data that contain rich information that is useful for the design of product service system. This paper presents a new framework that integrates a variety of artificial intelligence and machine learning techniques. All proposed operations of the framework can be realized based on the Google Cloud Platform. A case study is conducted to showcase the practical applicability of some key operations such as opinion mining. More than 40,000 customer reviews about the product Kindle White E-reader were analyzed.

Original language	English
Pages (from-to)	522-527
Number of pages	6
Journal	Procedia CIRP
Volume	83
DOIs	https://doi.org/10.1016/j.procir.2019.03.116
State	Published - 2019
Event	11th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2019 - Zhuhai, China Duration: 29 May 2019 → 31 May 2019

Keywords

Artifical intelrigance
Cloud computing
Customer review
Machine learning
Product service system

Access to Document

10.1016/j.procir.2019.03.116

Cite this

@article{0f2ab39d4ae64311a9a37213e1e796be,

title = "Analysis of customer reviews for product service system design based on cloud computing",

abstract = "Designing a product service system begins with understanding customer voices. Compared to the traditional methods such as survey, interview, customer review represents a particular kind of big data that contain rich information that is useful for the design of product service system. This paper presents a new framework that integrates a variety of artificial intelligence and machine learning techniques. All proposed operations of the framework can be realized based on the Google Cloud Platform. A case study is conducted to showcase the practical applicability of some key operations such as opinion mining. More than 40,000 customer reviews about the product Kindle White E-reader were analyzed.",

keywords = "Artifical intelrigance, Cloud computing, Customer review, Machine learning, Product service system",

author = "Diandi Chen and Dawen Zhang and Fei Tao and Ang Liu",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors. Published by Elsevier B.V.; 11th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2019 ; Conference date: 29-05-2019 Through 31-05-2019",

year = "2019",

doi = "10.1016/j.procir.2019.03.116",

language = "英语",

volume = "83",

pages = "522--527",

journal = "Procedia CIRP",

issn = "2212-8271",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Analysis of customer reviews for product service system design based on cloud computing

AU - Chen, Diandi

AU - Zhang, Dawen

AU - Tao, Fei

AU - Liu, Ang

PY - 2019

Y1 - 2019

N2 - Designing a product service system begins with understanding customer voices. Compared to the traditional methods such as survey, interview, customer review represents a particular kind of big data that contain rich information that is useful for the design of product service system. This paper presents a new framework that integrates a variety of artificial intelligence and machine learning techniques. All proposed operations of the framework can be realized based on the Google Cloud Platform. A case study is conducted to showcase the practical applicability of some key operations such as opinion mining. More than 40,000 customer reviews about the product Kindle White E-reader were analyzed.

AB - Designing a product service system begins with understanding customer voices. Compared to the traditional methods such as survey, interview, customer review represents a particular kind of big data that contain rich information that is useful for the design of product service system. This paper presents a new framework that integrates a variety of artificial intelligence and machine learning techniques. All proposed operations of the framework can be realized based on the Google Cloud Platform. A case study is conducted to showcase the practical applicability of some key operations such as opinion mining. More than 40,000 customer reviews about the product Kindle White E-reader were analyzed.

KW - Artifical intelrigance

KW - Cloud computing

KW - Customer review

KW - Machine learning

KW - Product service system

UR - https://www.scopus.com/pages/publications/85070559738

U2 - 10.1016/j.procir.2019.03.116

DO - 10.1016/j.procir.2019.03.116

M3 - 会议文章

AN - SCOPUS:85070559738

SN - 2212-8271

VL - 83

SP - 522

EP - 527

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 11th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2019

Y2 - 29 May 2019 through 31 May 2019

ER -

Analysis of customer reviews for product service system design based on cloud computing

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this