ICA k-means based time series clustering analysis of online word-of-mouth

Na Pan; Hong Li; Chunyang Liu

doi:10.1109/ICSSSM.2015.7170342

ICA k-means based time series clustering analysis of online word-of-mouth

Na Pan
, Hong Li
, Chunyang Liu^*

^*Corresponding author for this work

School of Economics and Management

Beihang University
National Computer Network Emergency Response Technical Team

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Online word-of-mouth activity is a very typical index of the lifecycle evolution model of a product, and understanding product lifecycle can help corresponding decision makers with their formulation of marketing strategies. In this paper, the data sets for the online comments on various types of products are studied; based on management theory and economics theory, and by applying such methods as independent component analysis (ICA) and clustering, the online word-of-mouth activities for different products or similar products are analyzed through clustering; meanwhile, the lifecycle curves for some representative products are extracted, and typical lifecycles are profoundly analyzed. This paper aims to effectively improve the effect of online word-of-mouth information on e-commerce marketing management and decision making, and to obtain internationally advanced achievement in corresponding field.

Original language	English
Title of host publication	2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479983285
DOIs	https://doi.org/10.1109/ICSSSM.2015.7170342
State	Published - 28 Jul 2015
Event	12th International Conference on Service Systems and Service Management, ICSSSM 2015 - Guangzhou, China Duration: 22 Jun 2015 → 24 Jun 2015

Publication series

Name	2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015

Conference

Conference	12th International Conference on Service Systems and Service Management, ICSSSM 2015
Country/Territory	China
City	Guangzhou
Period	22/06/15 → 24/06/15

Keywords

ICA
k-means
lifecycle
online word-of-mouth
time series clustering

Access to Document

10.1109/ICSSSM.2015.7170342

Cite this

Pan, N., Li, H., & Liu, C. (2015). ICA k-means based time series clustering analysis of online word-of-mouth. In 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015 Article 7170342 (2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSSSM.2015.7170342

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title = "ICA k-means based time series clustering analysis of online word-of-mouth",

abstract = "Online word-of-mouth activity is a very typical index of the lifecycle evolution model of a product, and understanding product lifecycle can help corresponding decision makers with their formulation of marketing strategies. In this paper, the data sets for the online comments on various types of products are studied; based on management theory and economics theory, and by applying such methods as independent component analysis (ICA) and clustering, the online word-of-mouth activities for different products or similar products are analyzed through clustering; meanwhile, the lifecycle curves for some representative products are extracted, and typical lifecycles are profoundly analyzed. This paper aims to effectively improve the effect of online word-of-mouth information on e-commerce marketing management and decision making, and to obtain internationally advanced achievement in corresponding field.",

keywords = "ICA, k-means, lifecycle, online word-of-mouth, time series clustering",

author = "Na Pan and Hong Li and Chunyang Liu",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th International Conference on Service Systems and Service Management, ICSSSM 2015 ; Conference date: 22-06-2015 Through 24-06-2015",

year = "2015",

month = jul,

day = "28",

doi = "10.1109/ICSSSM.2015.7170342",

language = "英语",

series = "2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015",

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}

Pan, N, Li, H & Liu, C 2015, ICA k-means based time series clustering analysis of online word-of-mouth. in 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015., 7170342, 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015, Institute of Electrical and Electronics Engineers Inc., 12th International Conference on Service Systems and Service Management, ICSSSM 2015, Guangzhou, China, 22/06/15. https://doi.org/10.1109/ICSSSM.2015.7170342

ICA k-means based time series clustering analysis of online word-of-mouth. / Pan, Na; Li, Hong; Liu, Chunyang.
2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7170342 (2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - ICA k-means based time series clustering analysis of online word-of-mouth

AU - Pan, Na

AU - Li, Hong

AU - Liu, Chunyang

PY - 2015/7/28

Y1 - 2015/7/28

N2 - Online word-of-mouth activity is a very typical index of the lifecycle evolution model of a product, and understanding product lifecycle can help corresponding decision makers with their formulation of marketing strategies. In this paper, the data sets for the online comments on various types of products are studied; based on management theory and economics theory, and by applying such methods as independent component analysis (ICA) and clustering, the online word-of-mouth activities for different products or similar products are analyzed through clustering; meanwhile, the lifecycle curves for some representative products are extracted, and typical lifecycles are profoundly analyzed. This paper aims to effectively improve the effect of online word-of-mouth information on e-commerce marketing management and decision making, and to obtain internationally advanced achievement in corresponding field.

AB - Online word-of-mouth activity is a very typical index of the lifecycle evolution model of a product, and understanding product lifecycle can help corresponding decision makers with their formulation of marketing strategies. In this paper, the data sets for the online comments on various types of products are studied; based on management theory and economics theory, and by applying such methods as independent component analysis (ICA) and clustering, the online word-of-mouth activities for different products or similar products are analyzed through clustering; meanwhile, the lifecycle curves for some representative products are extracted, and typical lifecycles are profoundly analyzed. This paper aims to effectively improve the effect of online word-of-mouth information on e-commerce marketing management and decision making, and to obtain internationally advanced achievement in corresponding field.

KW - ICA

KW - k-means

KW - lifecycle

KW - online word-of-mouth

KW - time series clustering

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M3 - 会议稿件

AN - SCOPUS:84948151182

T3 - 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015

BT - 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Pan N, Li H, Liu C. ICA k-means based time series clustering analysis of online word-of-mouth. In 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7170342. (2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015). doi: 10.1109/ICSSSM.2015.7170342

ICA k-means based time series clustering analysis of online word-of-mouth

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