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User modeling : through statistical analysis and an evolving classifier

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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Standard

User modeling : through statistical analysis and an evolving classifier. / Iglesias, Jose; Angelov, Plamen; Ledezma, Agapito; Sanchis, Araceli.

IEEE International Conference on Fuzzy Systems (FUZZ), 2010 . IEEE, 2010. p. 3226-3233.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Harvard

Iglesias, J, Angelov, P, Ledezma, A & Sanchis, A 2010, User modeling : through statistical analysis and an evolving classifier. in IEEE International Conference on Fuzzy Systems (FUZZ), 2010 . IEEE, pp. 3226-3233, IEEE World Congress on Computational Intelligence WCCI 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/FUZZY.2010.5584905

APA

Iglesias, J., Angelov, P., Ledezma, A., & Sanchis, A. (2010). User modeling : through statistical analysis and an evolving classifier. In IEEE International Conference on Fuzzy Systems (FUZZ), 2010 (pp. 3226-3233). IEEE. https://doi.org/10.1109/FUZZY.2010.5584905

Vancouver

Iglesias J, Angelov P, Ledezma A, Sanchis A. User modeling : through statistical analysis and an evolving classifier. In IEEE International Conference on Fuzzy Systems (FUZZ), 2010 . IEEE. 2010. p. 3226-3233 https://doi.org/10.1109/FUZZY.2010.5584905

Author

Iglesias, Jose ; Angelov, Plamen ; Ledezma, Agapito ; Sanchis, Araceli. / User modeling : through statistical analysis and an evolving classifier. IEEE International Conference on Fuzzy Systems (FUZZ), 2010 . IEEE, 2010. pp. 3226-3233

Bibtex

@inproceedings{86a84789584c46f3b0dbc5c884445b6c,
title = "User modeling : through statistical analysis and an evolving classifier",
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. (c) IEEE Press",
keywords = "evolving fuzzy behaviours, behavior modeling",
author = "Jose Iglesias and Plamen Angelov and Agapito Ledezma and Araceli Sanchis",
note = "{"}{\textcopyright}2010 IEEE. 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.{"} {"}This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.{"}; IEEE World Congress on Computational Intelligence WCCI 2010 ; Conference date: 18-07-2010 Through 23-07-2010",
year = "2010",
month = jul
doi = "10.1109/FUZZY.2010.5584905",
language = "English",
isbn = "978-1-4244-6919-2",
pages = "3226--3233",
booktitle = "IEEE International Conference on Fuzzy Systems (FUZZ), 2010",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - User modeling : through statistical analysis and an evolving classifier

AU - Iglesias, Jose

AU - Angelov, Plamen

AU - Ledezma, Agapito

AU - Sanchis, Araceli

N1 - "©2010 IEEE. 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." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."

PY - 2010/7

Y1 - 2010/7

N2 - 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. (c) IEEE Press

AB - 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. (c) IEEE Press

KW - evolving fuzzy behaviours

KW - behavior modeling

U2 - 10.1109/FUZZY.2010.5584905

DO - 10.1109/FUZZY.2010.5584905

M3 - Conference contribution/Paper

SN - 978-1-4244-6919-2

SP - 3226

EP - 3233

BT - IEEE International Conference on Fuzzy Systems (FUZZ), 2010

PB - IEEE

T2 - IEEE World Congress on Computational Intelligence WCCI 2010

Y2 - 18 July 2010 through 23 July 2010

ER -