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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/402

Title: Modeling human behavior in user-adaptive systems: Recent advances using soft computing techniques
Authors: Frias-Martinez, E
Magoulas, G
Chen, SY
Macredie, RD
Keywords: User modeling
Adaptive hypermedia
Soft computing
Machine learning
Data mining
Publication Date: 2005
Publisher: Elsevier
Citation: Expert Systems with Applications, 29(2): 320-329, Aug 2005
Abstract: Adaptive Hypermedia systems are becoming more important in our everyday activities and users are expecting more intelligent services from them. The key element of a generic adaptive hypermedia system is the user model. Traditional machine learning techniques used to create user models are usually too rigid to capture the inherent uncertainty of human behavior. In this context, soft computing techniques can be used to handle and process human uncertainty and to simulate human decision-making. This paper examines how soft computing techniques, including fuzzy logic, neural networks, genetic algorithms, fuzzy clustering and neuro-fuzzy systems, have been used, alone or in combination with other machine learning techniques, for user modeling from 1999 to 2004. For each technique, its main applications, limitations and future directions for user modeling are presented. The paper also presents guidelines that show which soft computing techniques should be used according to the task implemented by the application.
URI: http://www.sciencedirect.com/science/journal/09574174
http://bura.brunel.ac.uk/handle/2438/402
DOI: http://dx.doi.org/10.1016/j.eswa.2005.04.005
Appears in Collections:Information Systems and Computing
School of Information Systems, Computing and Mathematics Research Papers
Economics and Finance

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