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106 results on '"Gómez-Adorno, Helena"'

1. HyperLoader: Integrating Hypernetwork-Based LoRA and Adapter Layers into Multi-Task Transformers for Sequence Labelling

Author

Ortiz-Barajas, Jesus-German, Gomez-Adorno, Helena, and Solorio, Thamar

Subjects
Computer Science - Computation and Language
Abstract

We present HyperLoader, a simple approach that combines different parameter-efficient fine-tuning methods in a multi-task setting. To achieve this goal, our model uses a hypernetwork to generate the weights of these modules based on the task, the transformer layer, and its position within this layer. Our method combines the benefits of multi-task learning by capturing the structure of all tasks while reducing the task interference problem by encapsulating the task-specific knowledge in the generated weights and the benefits of combining different parameter-efficient methods to outperform full-fine tuning. We provide empirical evidence that HyperLoader outperforms previous approaches in most datasets and obtains the best average performance across tasks in high-resource and low-resource scenarios.

Published
2024

2. Statistical Evaluation of CESAMO Encoder for Pattern Preservation in Categorical Data

Author

Valdez-Valenzuela, Eric, Kuri-Morales, Angel, Gomez-Adorno, Helena, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Mezura-Montes, Efrén, editor, Acosta-Mesa, Héctor Gabriel, editor, Carrasco-Ochoa, Jesús Ariel, editor, Martínez-Trinidad, José Francisco, editor, and Olvera-López, José Arturo, editor

Published
2024
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3. Job Offers Classifier using Neural Networks and Oversampling Methods

Author

Ortiz, Germán, Enguix, Gemma Bel, Gómez-Adorno, Helena, Ameer, Iqra, and Sidorov, Grigori

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Both policy and research benefit from a better understanding of individuals' jobs. However, as large-scale administrative records are increasingly employed to represent labor market activity, new automatic methods to classify jobs will become necessary. We developed an automatic job offers classifier using a dataset collected from the largest job bank of Mexico known as Bumeran https://www.bumeran.com.mx/ Last visited: 19-01-2022.. We applied machine learning algorithms such as Support Vector Machines, Naive-Bayes, Logistic Regression, Random Forest, and deep learning Long-Short Term Memory (LSTM). Using these algorithms, we trained multi-class models to classify job offers in one of the 23 classes (not uniformly distributed): Sales, Administration, Call Center, Technology, Trades, Human Resources, Logistics, Marketing, Health, Gastronomy, Financing, Secretary, Production, Engineering, Education, Design, Legal, Construction, Insurance, Communication, Management, Foreign Trade, and Mining. We used the SMOTE, Geometric-SMOTE, and ADASYN synthetic oversampling algorithms to handle imbalanced classes. The proposed convolutional neural network architecture achieved the best results when applied the Geometric-SMOTE algorithm., Comment: 13 pages, 2 figures, 8th World Conference On Soft Computing

Published
2022

4. Mental Illness Classification on Social Media Texts using Deep Learning and Transfer Learning

Author

Ameer, Iqra, Arif, Muhammad, Sidorov, Grigori, Gòmez-Adorno, Helena, and Gelbukh, Alexander

Subjects
Computer Science - Machine Learning, Computer Science - Computation and Language, Computer Science - Computers and Society
Abstract

Given the current social distance restrictions across the world, most individuals now use social media as their major medium of communication. Millions of people suffering from mental diseases have been isolated due to this, and they are unable to get help in person. They have become more reliant on online venues to express themselves and seek advice on dealing with their mental disorders. According to the World health organization (WHO), approximately 450 million people are affected. Mental illnesses, such as depression, anxiety, etc., are immensely common and have affected an individuals' physical health. Recently Artificial Intelligence (AI) methods have been presented to help mental health providers, including psychiatrists and psychologists, in decision making based on patients' authentic information (e.g., medical records, behavioral data, social media utilization, etc.). AI innovations have demonstrated predominant execution in numerous real-world applications broadening from computer vision to healthcare. This study analyzes unstructured user data on the Reddit platform and classifies five common mental illnesses: depression, anxiety, bipolar disorder, ADHD, and PTSD. We trained traditional machine learning, deep learning, and transfer learning multi-class models to detect mental disorders of individuals. This effort will benefit the public health system by automating the detection process and informing appropriate authorities about people who require emergency assistance., Comment: 11 pages, 2 figures, 8th World Conference On Soft Computing

Published
2022

6. Descriptions of issues and comments for predicting issue success in software projects

Author

Ramírez-Mora, Sandra L., Oktaba, Hanna, and Gómez-Adorno, Helena

Subjects
Computer Science - Software Engineering
Abstract

Software development tasks must be performed successfully to achieve software quality and customer satisfaction. Knowing whether software tasks are likely to fail is essential to ensure the success of software projects. Issue Tracking Systems store information of software tasks (issues) and comments, which can be useful to predict issue success; however; almost no research on this topic exists. This work studies the usefulness of textual descriptions of issues and comments for predicting whether issues will be resolved successfully or not. Issues and comments of 588 software projects were extracted from four popular Issue Tracking Systems. Seven machine learning classifiers were trained on 30k issues and more than 120k comments, and more than 6000 experiments were performed to predict the success of three types of issues: bugs, improvements and new features. The results provided evidence that descriptions of issues and comments are useful for predicting issue success with more than 85% of accuracy and precision, and that the predictions of issue success vary over time. Words related to software development were particularly relevant for predicting issue success. Other communication aspects and their relationship to the success of software projects must be researched in detail using data from software tools., Comment: 65 pages; 15 figures

Published
2020
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8. CESAMMO: Categorical Encoding by Statistical Applied Multivariable Modeling

Author

Valdez-Valenzuela, Eric, Kuri-Morales, Angel, Gomez-Adorno, Helena, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Pichardo Lagunas, Obdulia, editor, Martínez-Miranda, Juan, editor, and Martínez Seis, Bella, editor

Published
2022
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9. Measuring the Effect of Categorical Encoders in Machine Learning Tasks Using Synthetic Data

Author

Valdez-Valenzuela, Eric, Kuri-Morales, Angel, Gomez-Adorno, Helena, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Batyrshin, Ildar, editor, Gelbukh, Alexander, editor, and Sidorov, Grigori, editor

Published
2021
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10. Evaluation of Similarity Measures in a Benchmark for Spanish Paraphrasing Detection : 19th Mexican International Conference on Artificial Intelligence

Author

Gómez-Adorno, Helena, Bel-Enguix, Gemma, Sierra, Gerardo, Torres-Moreno, Juan-Manuel, Martinez, Renata, Serrano, Pedro, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Martínez-Villaseñor, Lourdes, editor, Herrera-Alcántara, Oscar, editor, Ponce, Hiram, editor, and Castro-Espinoza, Félix A., editor

Published
2020
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11. Gender Identification in Social Media Using Transfer Learning

Author

Sotelo, Aquilino Francisco, Gómez-Adorno, Helena, Esquivel-Flores, Oscar, Bel-Enguix, Gemma, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Figueroa Mora, Karina Mariela, editor, Anzurez Marín, Juan, editor, Cerda, Jaime, editor, Carrasco-Ochoa, Jesús Ariel, editor, Martínez-Trinidad, José Francisco, editor, and Olvera-López, José Arturo, editor

Published
2020
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13. Hierarchical Clustering Analysis: The Best-Performing Approach at PAN 2017 Author Clustering Task

Author

Gómez-Adorno, Helena, Martín-del-Campo-Rodríguez, Carolina, Sidorov, Grigori, Alemán, Yuridiana, Vilariño, Darnes, Pinto, David, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Bellot, Patrice, editor, Trabelsi, Chiraz, editor, Mothe, Josiane, editor, Murtagh, Fionn, editor, Nie, Jian Yun, editor, Soulier, Laure, editor, SanJuan, Eric, editor, Cappellato, Linda, editor, and Ferro, Nicola, editor

Published
2018
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15. Comparison of Character n-grams and Lexical Features on Author, Gender, and Language Variety Identification on the Same Spanish News Corpus

Author

Sanchez-Perez, Miguel A., Markov, Ilia, Gómez-Adorno, Helena, Sidorov, Grigori, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Jones, Gareth J.F., editor, Lawless, Séamus, editor, Gonzalo, Julio, editor, Kelly, Liadh, editor, Goeuriot, Lorraine, editor, Mandl, Thomas, editor, Cappellato, Linda, editor, and Ferro, Nicola, editor

Published
2017
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16. Author Profiling with Doc2vec Neural Network-Based Document Embeddings

Author

Markov, Ilia, Gómez-Adorno, Helena, Posadas-Durán, Juan-Pablo, Sidorov, Grigori, Gelbukh, Alexander, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Pichardo-Lagunas, Obdulia, editor, and Miranda-Jiménez, Sabino, editor

Published
2017
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20. Overview of HOMO-MEX at Iberlef 2023: Hate speech detection in Online Messages directed Towards the MEXican Spanish speaking LGBTQ+ population.

Author

Bel-Enguix, Gemma, Gómez-Adorno, Helena, Sierra, Gerardo, Vásquez, Juan, Andersen, Scott Thomas, and Ojeda-Trueba, Sergio

Subjects
HATE speech, SPANISH language, NATURAL language processing, PHOBIAS, DEAF children
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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23. A Question Answering System for Reading Comprehension Tests

Author

Gómez-Adorno, Helena, Pinto, David, Vilariño, Darnes, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carrasco-Ochoa, Jesús Ariel, editor, Martínez-Trinidad, José Francisco, editor, Rodríguez, Joaquín Salas, editor, and di Baja, Gabriella Sanniti, editor

Published
2013
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24. Forecast of Air Quality Based on Ozone by Decision Trees and Neural Networks

Author

Loya, Nahun, Olmos Pineda, Iván, Pinto, David, Gómez-Adorno, Helena, Alemán, Yuridiana, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Batyrshin, Ildar, editor, and González Mendoza, Miguel, editor

Published
2013
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25. Resumen de PAR-MEX en IberLEF 2022: Tarea Compartida para la Detección de Paráfrasis en Español

Author

Bel Enguix, Gemma, Sierra Martínez, Gerardo, Gómez-Adorno, Helena, Torres Moreno, Juan Manuel, Ortiz-Barajas, Jesus-German, and Vásquez, Juan

Subjects
PAR-MEX, Iberlef, Detección paráfrasis, Paraphrase detection
Abstract

Paraphrase detection is an important unresolved task in natural language processing; especially in the Spanish language. In order to address this issue, and contribute to the creation of high-performance paraphrase detection automated systems, we propose a shared task called PAR-MEX. For this task, we created a corpus, in Spanish, with topics in the domain of Mexican gastronomy. Afterwards, the participants in this task submitted their classification results on our corpus. In this paper we explain the steps followed for the creation of the corpus, we summarize the results obtained by the various participants, and propose some conclusions regarding the paraphrase-detection task in Spanish. La detección de paráfrasis es una tarea importante no resuelta en procesamiento del lenguaje natural; especialmente en la lengua española. Para atacar este problema, y para contribuir a la creación de sistemas de detección automática que obtengan resultados competitivos, proponemos la tarea compartida llamada PAR-MEX. Para esto, creamos un corpus en español con temas dentro del campo semántico de gastronomía mexicana. Después los participantes en esta tarea enviaron los resultados de sus sistemas de clasificación sobre nuestro corpus. En este paper explicamos los pasos seguidos para la creación del corpus, resumimos los resultados obtenidos por los participantes, y proponemos algunas conclusiones al respecto de la detección de paráfrasis en español. We acknowledge the support of the projects CONACyT CB A1-S-27780, and DGAPA-UNAM PAPIIT references TA400121 and TA101722.

Published
2022

30. Overview of PAR-MEX at Iberlef 2022: Paraphrase Detection in Spanish Shared Task

Author

Bel Enguix, Gemma, Sierra Martínez, Gerardo, Gómez-Adorno, Helena, Torres Moreno, Juan Manuel, Ortiz-Barajas, Jesus-German, and Vásquez, Juan

Subjects
PAR-MEX, Iberlef, Detección paráfrasis, Paraphrase detection
Abstract

Paraphrase detection is an important unresolved task in natural language processing; especially in the Spanish language. In order to address this issue, and contribute to the creation of high-performance paraphrase detection automated systems, we propose a shared task called PAR-MEX. For this task, we created a corpus, in Spanish, with topics in the domain of Mexican gastronomy. Afterwards, the participants in this task submitted their classification results on our corpus. In this paper we explain the steps followed for the creation of the corpus, we summarize the results obtained by the various participants, and propose some conclusions regarding the paraphrase-detection task in Spanish. La detección de paráfrasis es una tarea importante no resuelta en procesamiento del lenguaje natural; especialmente en la lengua española. Para atacar este problema, y para contribuir a la creación de sistemas de detección automática que obtengan resultados competitivos, proponemos la tarea compartida llamada PAR-MEX. Para esto, creamos un corpus en español con temas dentro del campo semántico de gastronomía mexicana. Después los participantes en esta tarea enviaron los resultados de sus sistemas de clasificación sobre nuestro corpus. En este paper explicamos los pasos seguidos para la creación del corpus, resumimos los resultados obtenidos por los participantes, y proponemos algunas conclusiones al respecto de la detección de paráfrasis en español. We acknowledge the support of the projects CONACyT CB A1-S-27780, and DGAPA-UNAM PAPIIT references TA400121 and TA101722.

Published
2022

34. Overview of FakeDeS at IberLEF 2021: Fake News Detection in Spanish Shared Task

Author

Gómez-Adorno, Helena, Posadas-Durán, Juan Pablo, Bel Enguix, Gemma, and Porto Capetillo, Claudia

Subjects
Fake news detection, Iberlef, Lenguajes y Sistemas Informáticos, FakeDeS
Abstract

This paper presents the overview of FakeDeS 2021, the second edition of this lab under the IberLEF conference. The FakeDeS shared task aims to explore different methodologies and strategies related to fake news detection in Spanish. This year edition brings two main challenges: thematic and language variation. For this purpose, we introduce a new testing corpus containing news related to COVID-19 and news from other Ibero-American countries. Este artículo hace una presentación general de la tarea compartida FakeDeS 2021, cuya segunda edición ha tenido lugar en 2021 bajo el congreso IberLEF, aunque se trata de la primera vez con esta denominación. La tarea FakeDeS tiene por objetivo explorar diferentes métodos y estategias relacinados con la detección de noticias falsas en español, principalmente en su variante de México. La edición de este año propone dos desafíos principales: variación temática y variación lingüística. Para ello, se introduce un nuevo corpus de prueba que contiene noticias relacionadas con COVID 19 y noticias de otros países de Iber-América. This research was funded by CONACyT project CB A1-S-27780, DGAPA-UNAM PAPIIT grants number TA400121 and TA100520. The authors also thank CONACYT for the computer resources provided through the INAOE Supercomputing Laboratory's Deep Learning Platform for Language Technologies.

Published
2021

36. Overview of PAR-MEX at Iberlef 2022: Paraphrase Detection in Spanish Shared Task.

Author

Bel-Enguix, Gemma, Sierra, Gerardo, Gómez-Adorno, Helena, Torres-Moreno, Juan-Manuel, Ortiz-Barajas, Jesus-German, and Vásquez, Juan

Subjects
SPANISH language, NATURAL language processing, PARAPHRASE, TASKS
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2022
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39. Creating a corpus of historical documents for emotions identification.

Author

Vázquez-González, Stephanie, Somodevilla-García, María, López, Rosalva Loreto, Gómez-Adorno, Helena, Pinto, David, Beltrán, Beatriz, and Singh, Vivek

Subjects
HISTORICAL source material, DEEP learning, IDENTIFICATION documents, CORPORA, MACHINE learning, HISPANIC Americans
Abstract

The aim of this article is to contextualize and describe the gathering and annotation of a conventual Hispanic and Novo Hispanic texts corpus for emotions identification. Such corpus will be the dataset for an emotions identification model based on machine learning ∖ deep learning techniques. Furthermore, this document describes several exploratory experiments carried out on the corpus. Within these experiments, it is described how the corpus is also used to obtain a lexicon mapped to polarities and emotions, and how some of the documents are hand-labeled by experts for the evaluation of the Machine Learning ∖ Deep learning -based emotion classification model. Finally, the future uses and experiments with said corpus are described. [ABSTRACT FROM AUTHOR]

Published
2022
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40. A case study in authorship attribution: The Mondrigo1.

Author

Sierra, Gerardo, Hernández-García, Tonatiuh, Gómez-Adorno, Helena, Bel-Enguix, Gemma, Pinto, David, Beltrán, Beatriz, and Singh, Vivek

Subjects
ATTRIBUTION of authorship, STUDENT strikes, K-means clustering, STUDENT government, AUTHORSHIP
Abstract

In this paper, we present authorship attribution methods applied to ¡El Mondrigo! (1968), a controversial text supposedly created by order of the Mexican Government to defame a student strike. Up to now, although the authorship of the book has been attributed to several journalists and writers, it could not be demonstrated and remains an open problem. The work aims at establishing which one of the most commonly attributed writers is the real author. To do that, we implement methods based on stylometric features using textual distance, supervised, and unsupervised learning. The distance-based methods implemented in this work are Kilgarriff and Delta of Burrows, an SVM algorithm is used as the supervised method, and the k-means algorithm as the unsupervised algorithm. The applied methods were consistent by pointing out a single author as the most likely one. [ABSTRACT FROM AUTHOR]

Published
2022
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