Noticias

El artículo  A semantic data lake framework for autonomous fault management in SDN environments, por Fernando Benayas, Álvaro Carrera, Carlos A. Iglesias y Manuel García Amado has sido aceptado y publicado en la revista Transactions on Emerging Telecommunications Technologies. Esta revista se encuentra indexada en JCR: (Q3, 1.61).

 

Fault Management is a vital issue for any network operator since the beginning of the telecommunications era. As networks have become more and more complex, their management systems are crucial for any operator company. In this ecosystem, the Software‐Defined Networking (SDN) approach has appeared as a possible solution for different networking issues. The flexibility provided by SDN to the network management enables a great dynamism in the configuration of network devices. However, this feature introduces the cost of a potential increase in failures because every modification introduced on the control plane is a new possibility for failures to appear and cause a decrement of the quality for offered services. Because of the growing pace of the networks, the classical approach is not feasible to cope that dynamism. Increasing the number of human operators in charge of the fault management process would increase the operation cost dramatically. Thus, this paper presents an approach to apply machine learning over a big data framework for an autonomous fault management process in SDN networks. In this paper, we present a Semantic Data Lake framework for a self‐diagnosis service, which is deployed on top of an SDN management platform. Moreover, we have developed a prototype of the proposed service with different diagnosis models for SDN networks. Models and algorithms have been evaluated showing good results.

 

Referencia:

Benayas F, Carrera Á, García-Amado M, Iglesias CA. A semantic data lake framework for autonomous fault management in SDN environments. Trans Emerging Tel Tech. 2019; e3629. https: //doi.org/10.1002/ett.3629

 

Green Open Access:

http://gsi.upm.es/administrator/components/com_jresearch/files/publications/prerprint%20with%20acknow-SDS2018_SI.pdf

 El grupo de Sistemas Inteligentes organiza un acto de entrega de la Primera Edición de las Becas  de Iniciación a la investigación en Sistemas Inteligentes:

  • Beca Profesor Gregorio Fernández de Iniciación a la Investigación en aprendizaje automático y Big Data
  • Beca Profesora Mercedes Garijo de Iniciación a la Investigación en tecnología de agentes
  • Beca Profesor Fernando Sáez-Vacas de Iniciación a la investigación en complejidad y sistemas sociales
Lugar: Edificio C, Sala de Profesores, C--201
Cuándo: Lunes, 29 de abril, 11:30h
Duración: 1 hora
 
El acto será presidido por el Rector de la Universidad Politécnica de Madrid, Guillermo Cisneros, el Director de la ETSIT, Félix Pérez, y la Directora del DIT, Encarna Pastor. En el acto se entregarán las becas de la primera edición, e intervendrán varios miembros del grupo de investigación para recordar aspectos de los tres  profesores fundadores del grupo.
 
 
Media hora antes, a las 11h, se descubrirá la placa homenaje en la puerta del laboratorio de invesetigación del DIT C-215 con el nombre de los tres profesores.

El artículo A framework for fake review detection in online consumer electronics retailers, por Rodrigo Barbado, Oscar Araque y Carlos A. Iglesias has sido aceptado y publicado en la revista Information Processing & Management. Esta revista se encuentra indexada en JCR: (Q1, 3.444).

 

Abstract:The impact of online reviews on businesses has grown significantly during last years, being crucial to determine business success in a wide array of sectors, ranging from restaurants, hotels to e-commerce. Unfortunately, some users use unethical means to improve their online reputation by writing fake reviews of their businesses or competitors. Previous research has addressed fake review detection in a number of domains, such as product or business reviews in restaurants and hotels. However, in spite of its economical interest, the domain of consumer electronics businesses has not yet been thoroughly studied. This article proposes a feature framework for detecting fake reviews that has been evaluated in the consumer electronics domain. The contributions are fourfold: (i) Construction of a dataset for classifying fake reviews in the consumer electronics domain in four different cities based on scraping techniques; (ii) definition of a feature framework for fake review detection; (iii) development of a fake review classification method based on the proposed framework and (iv) evaluation and analysis of the results for each of the cities under study. We have reached an 82% F-Score on the classification task and the Ada Boost classifier has been proven to be the best one by statistical means according to the Friedman test.

 

Referencia:

Oscar Araque, Ganggao Zhu, Carlos A. Iglesias, A semantic similarity-based perspective of affect lexicons for sentiment analysis, Knowledge-Based Systems, Volume 165, 2019, Pages 346-359, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2018.12.005. (http://www.sciencedirect.com/science/article/pii/S0950705118305926).

 
Green Open Access:

Este lunes 11 de febrero  de 2019 se ha celebrado el acto de entrega de premios en el Paraninfo de la Universidad Politécnica de Madrid de la III convocatoria de premios de la Cátedra Ingeniero General. D. Antonio Remón y Zarco del Valle.

Felicidades a Tasio Méndez que ha recibido el primer premio A la mejor tecnología, producto o servicio desarrollada en la UPM con temática relacionada con Defensa y Seguridad por su Trabajo de Fin de Grado titulado "Design and implementation of a visualization module for agent-based social simulations applied to radicalism spread".