DocumentCode :
3378867
Title :
Intelligent Customer Relationship Management on The Web
Author :
Wong, Kok Wai ; Fung, Chun Che ; Xiao, Xiong ; Wong, Kit Po
Author_Institution :
Sch. of Inf. Technol., Murdoch Univ., Murdoch, WA
fYear :
2005
fDate :
21-24 Nov. 2005
Firstpage :
1
Lastpage :
5
Abstract :
Customer relationship management using Web personalisation initiatives have gained much attention. The most important strategy of Web personalisation is to provide the customers with correct information or services based on the knowledge about the customers´ preferences. With the help of data mining technologies, the above strategy can be implemented. Computational intelligence technologies are investigated in this paper to provide interaction through Web personalisation. This paper proposed two algorithms for the personalisation of the online shopping websites. It uses the radial basis function (RBF) neural network. The algorithms first model the customer´s preferences as a complex nonlinear function. It personalises the information presented to customers based on their preferences. The second is the preference learning algorithm. It learns the customer´s preferences implicitly from the customer´s behaviours by using a RBF neural network.
Keywords :
Internet; customer relationship management; data mining; learning (artificial intelligence); radial basis function networks; retail data processing; Web personalisation; complex nonlinear function; computational intelligence technologies; customers preferences; data mining technologies; intelligent customer relationship management; online shopping Web sites; preference learning algorithm; radial basis function neural network; Artificial neural networks; Customer profiles; Customer relationship management; Data mining; Databases; Electronic commerce; Information filtering; Information filters; Internet; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
Type :
conf
DOI :
10.1109/TENCON.2005.301163
Filename :
4085031
Link To Document :
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