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Intelligent customer relationship management on the Web

Wong, K.W., Fung, C.C., Xaio, X. and Wong, K.P. (2005) Intelligent customer relationship management on the Web. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21-24 Nov. 2005, Melbourne, Vic. pp. 1-5.

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    Link to Published Version: http://dx.doi.org/10.1109/TENCON.2005.301163
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    Abstract

    In recent years, 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.

    Publication Type: Conference Paper
    Murdoch Affiliation: School of Information Technology
    Publisher: IEEE
    Copyright: (c) 2005 IEEE.
    Notes: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    URI: http://researchrepository.murdoch.edu.au/id/eprint/607
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