Browsing by Author "Fdez-Riverola, Florentino"
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- Active and Assisted Living Ecosystem for the ElderlyPublication . Marcelino, Isabel; Laza, Rosalía; Domingues, Patrício; Gómez-Meire, Silvana; Fdez-Riverola, Florentino; Pereira, AntónioA novel ecosystem to promote the physical, emotional and psychic health and well-being of the elderly is presented. Our proposal was designed to add several services developed to meet the needs of the senior population, namely services to improve social inclusion and increase contribution to society. Moreover, the solution monitors the vital signs of elderly individuals, as well as environmental parameters and behavior patterns, in order to seek eminent danger situations and predict potential hazardous issues, acting in accordance with the various alert levels specified for each individual. The platform was tested by seniors in a real scenario. The experimental results demonstrated that the proposed ecosystem was well accepted and is easy to use by seniors.
- RuleSIM: a toolkit for simulating the operation and improving throughput of rule-based spam filtersPublication . Ruano-Ordás, David; Fdez-Glez, Jorge; Fdez-Riverola, Florentino; Basto-Fernandes, Vitor; Méndez, José RamónThis paper introduces RuleSIM, a toolkit comprising different simulation tools specifically designed to aid researchers concerned about spam-filtering throughput. RuleSIM allows easily designing, developing, simulating and comparing new scheduling heuristics using different filters and sets of e-mails. Simulation results can be both graphically analysed, by using different complementary views, and quantitatively compared through several measures. Moreover, the underlying RuleSIM API can be easily integrated with third-party Java optimization platforms to facilitate debugging and achieve better configurations for rule scheduling. RuleSIM is free software distributed under the terms of GNU Lesser General Public License, and both source code and documentation are publicly available at https://github.com/rulesim/v2.0. Copyright © 2015 John Wiley & Sons, Ltd.
- A spam filtering multi-objective optimization study covering parsimony maximization and three-way classificationPublication . Basto-Fernandes, Vitor; Yevseyeva, Iryna; Méndez, José R.; Zhao, Jiaqi; Fdez-Riverola, Florentino; Emmerich, Michael T.M.Classifier performance optimization in machine learning can be stated as a multi-objective optimization problem. In this context, recent works have shown the utility of simple evolutionary multi-objective algorithms (NSGA-II, SPEA2) to conveniently optimize the global performance of different anti-spam filters. The present work extends existing contributions in the spam filtering domain by using three novel indicator-based (SMS-EMOA, CH-EMOA) and decomposition-based (MOEA/D) evolutionary multiobjective algorithms. The proposed approaches are used to optimize the performance of a heterogeneous ensemble of classifiers into two different but complementary scenarios: parsimony maximization and e-mail classification under low confidence level. Experimental results using a publicly available standard corpus allowed us to identify interesting conclusions regarding both the utility of rule-based classification filters and the appropriateness of a three-way classification system in the spam filtering domain.