Title :
ICA k-means based time series clustering analysis of online word-of-mouth
Author :
Na Pan ; Hong Li ; Chunyang Liu
Author_Institution :
Sch. of Econ. & Manage., Beihang Univ., Beijing, China
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 :
Internet; decision making; electronic commerce; independent component analysis; marketing; pattern clustering; product life cycle management; time series; ICA k-means based time series clustering analysis; decision maker; decision making; e-commerce marketing management; economics theory; independent component analysis; lifecycle curve; lifecycle evolution model; management theory; marketing strategy; online word-of-mouth information; product lifecycle; Algorithm design and analysis; Analytical models; Clustering algorithms; Clustering methods; Data mining; Signal processing algorithms; Time series analysis; ICA; k-means; lifecycle; online word-of-mouth; time series clustering;
Conference_Titel :
Service Systems and Service Management (ICSSSM), 2015 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-8327-8
DOI :
10.1109/ICSSSM.2015.7170342
