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    Modeling human behavior in user-adaptive systems: recent advances using soft computing techniques

    Frias-Martinez, E. and Magoulas, George D. and Chen, S. and Macredie, R. (2005) Modeling human behavior in user-adaptive systems: recent advances using soft computing techniques. Expert Systems with Applications 29 (2), pp. 320-329. ISSN 0957-4174.

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    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.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): User modeling, adaptive hypermedia, soft computing, machine learning, data mining
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Sandra Plummer
    Date Deposited: 01 Feb 2006
    Last Modified: 02 Dec 2016 13:23
    URI: http://eprints.bbk.ac.uk/id/eprint/311

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