Adaptive interaction for mass customization

Uchyigit, G. (2009) Adaptive interaction for mass customization In: Marlous, C. and Germanakos, P., eds. Mass Customization for Personalized Communication Environments: Integrating Human Factors. IGI Global, pp. 133-148. ISBN 9781605662602

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Abstract

The popularisation of mass customization and the need for integration of the user needs into the design, production and marketing phases has called for more innovative methods to be introduced into this area. At present the continuous growth of the world wide web and its rapid integration into people’s everyday lives and the popularisation of new technologies such as ubiquitous computing making possible the computing everywhere paradigm, offers a more desirable alternative for vendors in reaching their customers using more innovative techniques in an attempt to provide each customer with a one-to-one design, manufacturing and marketing service. The integration of ubiquitous computing technologies with machine learning and data mining techniques, which has been popular in personalization techniques, will serve to bring about innovative changes in this area. In future years this may revolutionise the way in which vendors can reach their customers offering every customer a tailored one-to-one service from design, to manufacturing, to delivery. This chapter will present the state of the art techniques to enable the combination of machine learning, data mining and ubiquitous computing technologies which will serve to provide innovative techniques applications and user interfaces for mass customization systems. This is currently a field of intense research and development activity and some technologies are already on the path to practical application. This chapter will present a state of the art survey of these technologies and their applications.

Item Type: Chapter in book
Subjects: G000 Computing and Mathematical Sciences > G400 Computing
DOI (a stable link to the resource): 10.4018/978-1-60566-260-2.ch008
Faculties: Faculty of Science and Engineering > School of Computing, Engineering and Mathematics > Computational Intelligence
Depositing User: editor cmis
Date Deposited: 31 May 2011 10:48
Last Modified: 10 Nov 2014 09:34
URI: http://eprints.brighton.ac.uk/id/eprint/8638

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