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Overview of the eHealth Knowledge Discovery Challenge at IberLEF 2019
This research has been partially supported by the University of Alicante and University of Havana, the Generalitat Valenciana (Conselleria d’Educacio, Investigacio, Cultura i Esport) and the Spanish
Evolution strategies with thresheld convergence
TLDR
This paper addresses the design of thresheld convergence in the context of evolution strategies by analyzing the behavior of the standard (μ, λ)-ES on multi-modal landscapes and arguing that part of it's shortcomings are due to an ineffective balance between exploration and exploitation.
Overview of TASS 2018: Opinions, Health and Emotions
This work has been partially supported by a grant from the Fondo Europeo de Desarrollo Regional (FEDER), the projects REDES (TIN2015-65136-C2-1-R, TIN2015-65136-C2-2-R) and SMART-DASCI
TASS 2018: The Strength of Deep Learning in Language Understanding Tasks
TLDR
Two new tasks focused on semantic relation extraction in the health domain and emotion classification in the news domain were added to the two traditional tasks of TASS, namely sentiment analysis at tweet level and aspect level.
Differential evolution with thresheld convergence
TLDR
This paper presents a new adaptive thresheld convergence mechanism which helps DE achieve large performance improvements in multi-modal search spaces.
A General-Purpose Annotation Model for Knowledge Discovery: Case Study in Spanish Clinical Text
TLDR
The structure of the annotations model is presented, with examples of annotated sentences and a brief description of each semantic role and relation defined, and the presented annotation model is extensible to other domains and languages.
Knowledge Discovery in COVID-19 Research Literature
TLDR
The preliminary results show that general-purpose semantic models are a useful tool for discovering fine-grained knowledge in large corpora of scientific documents in the COVID-19 pandemic.
Detección De Idioma En Twitter (Language Detection on Twitter)
TLDR
The results indicate that the axes of technological surveillance are applied in the selected universities, emphasizing the following elements of study: competitive surveillance, commercial surveillance, technological surveillance itself and surveillance of the environment.
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