M. Vega

Publications28
h-index8
Citations210
Highly Influential Citations6
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The learning vector quantization algorithm applied to automatic text classification tasks
TLDR
A neural approach to develop a text classifier based on the Learning Vector Quantization (LVQ) algorithm that has been applied to two specific tasks: text categorization and word sense disambiguation. Expand
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… Expand
Comparing Several Textual Information Retrieval Systems for the Geographical Information Retrieval Task
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. Expand
SINAI at WePS-3: Online Reputation Management
TLDR
A promising system, with a very good precision and easily extensible with the addition of new rules and other Internet resources, developed by the SINAI research group at the WEPS-3 task, called Online Reputation Management is presented. Expand
LVQ for text categorization using a multilingual linguistic resource
TLDR
This paper presents a multilingual categorization system based on neural learning, using the polyglot Bible as training collection, both in Spanish and English, based on using the LVQ algorithm to build a classifier that learns the training multilingual collection. Expand
Overview of TASS 2019: One More Further for the Global Spanish Sentiment Analysis Corpus
TLDR
This paper summarizes the approaches and the results of the submitted systems of the different groups for each task in the TASS workshop, and proposes a new approach to sentiment analysis at tweet level. Expand
The democratization of deep learning in TASS 2017
This research work is partially supported by REDES project (TIN2015-65136-C2-1-R) and SMART project (TIN2017-89517-P) from the Spanish Government, and a grant from the Fondo Europeo de Desarrollo… Expand
GEOUJA System. The First Participation of the University of Jaén at GEOCLEF 2006
Filtering for Improving the Geographic Information Search
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