DocumentCode :
2316066
Title :
User modeling: Through statistical analysis and an evolving classifier
Author :
Iglesias, Jose A. ; Angelov, Plamen ; Ledezma, Agapito ; Sanchis, Araceli
Author_Institution :
CAOS Group, Carlos III Univ. of Madrid, Leganes, Spain
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
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.
Keywords :
pattern classification; statistical analysis; user modelling; computer user behavior profile; evolving systems; statistical analysis; user modeling; user profile classifier; Computational modeling; Computers; Equations; Hidden Markov models; Libraries; Mathematical model; Prototypes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584905
Filename :
5584905
Link To Document :
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