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Data Mining for User Modeling

Data Mining for User Modeling

Jose Antonio Iglesias Martinez, Agapito Ledezma Espino, Araceli Sanchis de Miguel
Copyright: © 2012 |Volume: 3 |Issue: 1 |Pages: 17
ISSN: 1947-9344|EISSN: 1947-9352|EISBN13: 9781466613850|DOI: 10.4018/joci.2012010103
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MLA

Martinez, Jose Antonio Iglesias, et al. "Data Mining for User Modeling." IJOCI vol.3, no.1 2012: pp.35-51. http://doi.org/10.4018/joci.2012010103

APA

Martinez, J. A., Espino, A. L., & Sanchis de Miguel, A. (2012). Data Mining for User Modeling. International Journal of Organizational and Collective Intelligence (IJOCI), 3(1), 35-51. http://doi.org/10.4018/joci.2012010103

Chicago

Martinez, Jose Antonio Iglesias, Agapito Ledezma Espino, and Araceli Sanchis de Miguel. "Data Mining for User Modeling," International Journal of Organizational and Collective Intelligence (IJOCI) 3, no.1: 35-51. http://doi.org/10.4018/joci.2012010103

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Abstract

Nowadays, the systems that interact with the user, including computers, are improving very quickly. In this improvement, a great goal for the near future is to create systems able to adapt its behavior according to the needs of a particular user. The key element for this purpose is the user model. In this context, a goal of user modeling is to increase the effective use of computers and many other systems that require more sophistication in its interaction with the user. To achieve this goal, it is necessary to know how the users behave. Then, the anticipation of certain aspects of human behavior, such as goals, actions or preferences is possible. In this article, the development of user models using soft computing is presented. The main approaches to different user modeling are reviewed, and the main techniques used to develop user models are discussed. Also, a particular example is explained in detail.

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