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5 results on '"Ferreira-Santiago, Ángel"'

4. Feature Selection using Associative Memory Paradigm and Parallel Computing

Author

Aldape-Pérez, Mario, Cornelio Yanez-Marquez, Camacho-Nieto, Oscar, and Ferreira-Santiago, Ángel

Subjects
associative memory, pattern classification, Feature selection, Computación
Abstract

"Performance of most pattern classifiers is improved when redundant or irrelevant features are removed. Nevertheless, this is mainly achieved by highly demanding computational methods or successive classifiers’ construction. This paper shows how the associative memory paradigm and parallel computing can be used to perform Feature Selection tasks. This approach uses associative memories in order to get a mask value which represents a subset of features which clearly identifies irrelevant or redundant information for classification purposes. The performance of the proposed associative memory algorithm is validated by comparing classification accuracy of the suggested model against the performance achieved by other well-known algorithms. Experimental results show that associative memories can be implemented in parallel computing infrastructure, reducing the computational costs needed to find an optimal subset of features which maximizes classification performance"

Published
2013

5. Enhancing Engineering Education through Link Prediction in Social Networks.

Author

Ferreira-Santiago, Ángel, Yáñez-Márquez, Cornelio, López-Yáñez, Itzamá, Camacho-Nieto, Oscar, Aldape-Pérez, Mario, and Argüelles-Cruz, Amadeo-José

Subjects
ENGINEERING education, ONLINE social networks software, COMPUTER science literature, SYSTEMATIC instruction, ENGINEERING software, PUBLISHING
Abstract

In recent years the world has been a witness to a brutal onslaught of emergent technologies. As such it is not surprising that social networking has permeated through practically every human activity with amazing speed. Educational systems have not lagged behind; and not only is that true, but it is also evident that social networks have ostensibly penetrated in engineering education. This relevant and irrefutable fact has generated the necessity of posing systematic research activities on a worldwide scale that are related to this topic. In this context the topic covered in this paper is Social Network Research related to Engineering Education. Specifically, our research concerns the way or ways in which link prediction in social networks is able to improve teaching-learning processes in engineering education. A suitably natural environment for the application of such research is that of scholarly publications related to computer science, particularly networks. The results of our research are promising; they facilitate valuable information regarding the tendencies of the actors immersed in engineering education, be they students or faculty members. [ABSTRACT FROM AUTHOR]

Published
2016

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