Early Detection of Depression and Eating Disorders in Spanish: UNSL at MentalRiskES 2023

MentalRiskES is a novel challenge that proposes to solve problems related to early risk detection for the Spanish language. The objective is to detect, as soon as possible, Telegram users who show signs of mental disorders considering different tasks. Task 1 involved the users' detection of eating disorders, Task 2 focused on depression detection, and Task 3 aimed at detecting an unknown disorder. These tasks were divided into subtasks, each one defining a resolution approach. Our research group participated in subtask A for Tasks 1 and 2: a binary classification problem that evaluated whether the users were positive or negative. To solve these tasks, we proposed models based on Transformers followed by a decision policy according to criteria defined by an early detection framework. One of the models presented an extended vocabulary with important words for each task to be solved. In addition, we applied a decision policy based on the history of predictions that the model performs during user evaluation. For Tasks 1 and 2, we obtained the second-best performance according to rankings based on classification and latency, demonstrating the effectiveness and consistency of our approaches for solving early detection problems in the Spanish language.Comment: In Iberian Languages Evaluation Forum (IberLEF 2023), Ja\'en, Spai

Defeasible decision making in a robotic environment

Decision making models for autonomous agents are recently receiving increased attention, particularly in the feld of intelligent robots. This work presents a Defeasible Logic Programming approach to decision making in an environment with single and multiple robots. We will show, how a successful tool for knowledge representation and defeasible reasoning could be applied to the problem of deciding which task should be performed next. Besides, we will explain with detailed examples how the decision process is performed when there is only one robot in the environment, and then we will consider how the same robot decides when there are more robots working in the environment.Actualmente, los modelos de toma de decisiones para agentes autónomos están recibiendo mucha atención, particularmente en el área de robots inteligentes. Este trabajo presenta un enfoque basado en Programación en Lógica Rebatible para la toma de decisiones en un ambiente con un único robot y con múltiples robots. Mostraremos como una herramienta exitosa para la representación de conocimiento y razonamiento rebatible, puede ser aplicada al problema de decidir que tarea debe ser realizada a continuación. Además, explicaremos con ejemplos detallados como se realiza el proceso de decisión cuando hay solamente un robot en el ambiente, y luego consideraremos como decide el mismo robot cuando hay otros robots presentes en el ambiente.VIII Workshop de Procesamiento Distribuido y ParaleloRed de Universidades con Carreras en Informática (RedUNCI

Strategies to Harness the Transformers' Potential: UNSL at eRisk 2023

The CLEF eRisk Laboratory explores solutions to different tasks related to risk detection on the Internet. In the 2023 edition, Task 1 consisted of searching for symptoms of depression, the objective of which was to extract user writings according to their relevance to the BDI Questionnaire symptoms. Task 2 was related to the problem of early detection of pathological gambling risks, where the participants had to detect users at risk as quickly as possible. Finally, Task 3 consisted of estimating the severity levels of signs of eating disorders. Our research group participated in the first two tasks, proposing solutions based on Transformers. For Task 1, we applied different approaches that can be interesting in information retrieval tasks. Two proposals were based on the similarity of contextualized embedding vectors, and the other one was based on prompting, an attractive current technique of machine learning. For Task 2, we proposed three fine-tuned models followed by decision policy according to criteria defined by an early detection framework. One model presented extended vocabulary with important words to the addressed domain. In the last task, we obtained good performances considering the decision-based metrics, ranking-based metrics, and runtime. In this work, we explore different ways to deploy the predictive potential of Transformers in eRisk tasks.Comment: In Conference and Labs of the Evaluation Forum (CLEF 2023), Thessaloniki, Greec

A support for remote process execution in a load-balanced distributed system

Load distribution and balancing in a workstation-based network includes a number of intricate tasks. Among them, transparent remote process execution is an essential one. This work describes the main problems to be considered when implementing remote process execution and propose a design for an alternative system attempting to solve these problems.Eje: Sistemas distribuidosRed de Universidades con Carreras en Informática (RedUNCI

Exploratory Analysis of a New Corpus for Political Alignment Identification of Argentinian Journalists

Political alignment identification is an author profiling task that aims at identifying political bias/orientation in people’ writings. As usual in this kind of field, a key aspect is to have available adequate data sets so that the data mining and machine learning approaches can obtain reliable and informative results. This article takes a step in this direction by introducing a new corpus for the study of political alignment in documents of Argentinian journalists. The study also includes several kinds of analysis of documents of pro-government and opposition journalists such as sentiment analysis, topic modelling and the analysis of psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count (LIWC) system. From the experimental results, interesting patterns could be observed such as the topics both types of journalists write about, how the sentiment polarities are distributed and how the writings of pro-government and opposition journalists differ in the distinct LIWC categories.XVI Workshop Bases de Datos y Minería de Datos.Red de Universidades con Carreras en Informátic

Exploratory Analysis of a New Corpus for Political Alignment Identification of Argentinian Journalists

Political alignment identification is an author profiling task that aims at identifying political bias/orientation in people’ writings. As usual in this kind of field, a key aspect is to have available adequate data sets so that the data mining and machine learning approaches can obtain reliable and informative results. This article takes a step in this direction by introducing a new corpus for the study of political alignment in documents of Argentinian journalists. The study also includes several kinds of analysis of documents of pro-government and opposition journalists such as sentiment analysis, topic modelling and the analysis of psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count (LIWC) system. From the experimental results, interesting patterns could be observed such as the topics both types of journalists write about, how the sentiment polarities are distributed and how the writings of pro-government and opposition journalists differ in the distinct LIWC categories.XVI Workshop Bases de Datos y Minería de Datos.Red de Universidades con Carreras en Informátic