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Please use this identifier to cite or link to this item: http://hdl.handle.net/10016/10479

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Title: User modeling: through statistical analysis and an evolving classifier
Author(s): Iglesias, José Antonio
Angelov, Plamen
Ledezma, Agapito
Sanchis, Araceli
Publisher: IEEE
Issued date: 2010
Citation: 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 3226-3233.
URI: http://hdl.handle.net/10016/10479
ISBN: 978-1-4244-6919-2
ISSN: 1098-7584
DOI: http://dx.doi.org/10.1109/FUZZY.2010.5584905
Description: Proceeding of: 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) in the 2010 IEEE World Congress on Computational Intelligence (WCCI 2010). Barcelona, Spain, July, 18th - 23th, 2010.
Abstract: Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, an approach for creating and recognizing automatically the behavior profile of a computer user is combined with an evolving method to keep up to date the created profiles. The behavior of a computer is represented in this research as the sequence of commands s/he types during a period of time. This sequence is treated using statistical methods in order to create the corresponding user profile. However, as a user profile is usually not fixed but rather it changes and evolves, we propose a user profile classifier based on Evolving Systems. This paper describes briefly the model creation method and the evolving classifier, which are compared with well established off-line and on-line classifiers.
Publisher version: http://dx.doi.org/10.1109/FUZZY.2010.5584905
Keywords: Evolving fuzzy behaviours
Behavior modeling
Rights: © IEEE
Appears in Collections:DI - CAOS - Comunicaciones en Congresos y otros eventos

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