Search Results for author: Suilan Estevez-Velarde

Found 8 papers, 0 papers with code

Active Learning for Assisted Corpus Construction: A Case Study in Knowledge Discovery from Biomedical Text

no code implementations RANLP 2021 Hian Cañizares-Díaz, Alejandro Piad-Morffis, Suilan Estevez-Velarde, Yoan Gutiérrez, Yudivián Almeida Cruz, Andres Montoyo, Rafael Muñoz-Guillena

Experimental results suggest that the query strategy reduces by between 35% and 40% the number of sentences that must be manually annotated to develop systems able to reach a target F1 score, while the pre-annotation strategy produces an additional 24% reduction in the total annotation time.

Active Learning Sentence Embeddings

Knowledge Discovery in COVID-19 Research Literature

no code implementations RANLP 2021 Alejandro Piad-Morffis, Suilan Estevez-Velarde, Ernesto Luis Estevanell-Valladares, Yoan Gutiérrez, Andrés Montoyo, Rafael Muñoz, Yudivián Almeida-Cruz

This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic.

Automatic Discovery of Heterogeneous Machine Learning Pipelines: An Application to Natural Language Processing

no code implementations COLING 2020 Suilan Estevez-Velarde, Yoan Guti{\'e}rrez, Andres Montoyo, Yudivi{\'a}n Almeida Cruz

The system is freely available and includes in-built compatibility with a large number of popular machine learning frameworks, which makes our approach useful for solving practical problems with relative ease and effort.


Demo Application for LETO: Learning Engine Through Ontologies

no code implementations RANLP 2019 Suilan Estevez-Velarde, Andr{\'e}s Montoyo, Yudivian Almeida-Cruz, Yoan Guti{\'e}rrez, Alej Piad-Morffis, ro, Rafael Mu{\~n}oz

The massive amount of multi-formatted information available on the Web necessitates the design of software systems that leverage this information to obtain knowledge that is valid and useful.

A Neural Network Component for Knowledge-Based Semantic Representations of Text

no code implementations RANLP 2019 Alej Piad-Morffis, ro, Rafael Mu{\~n}oz, Yoan Guti{\'e}rrez, Yudivian Almeida-Cruz, Suilan Estevez-Velarde, Andr{\'e}s Montoyo

SNNs can be trained to encode explicit semantic knowledge from an arbitrary knowledge base, and can subsequently be combined with other deep learning architectures.

Opinion Mining

AutoML Strategy Based on Grammatical Evolution: A Case Study about Knowledge Discovery from Text

no code implementations ACL 2019 Suilan Estevez-Velarde, Yoan Guti{\'e}rrez, Andr{\'e}s Montoyo, Yudivi{\'a}n Almeida-Cruz

The process of extracting knowledge from natural language text poses a complex problem that requires both a combination of machine learning techniques and proper feature selection.

AutoML feature selection

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