Enseñanza de Inteligencia Artificial en el Nivel Introductorio: Fundamentos, Énfasis y Restricciones

A partir de una consideración previa de contenidos fundamentales se propone en este trabajo el programa para un curso introductorio de Inteligencia Artificial con énfasis en Razonamiento y Acción. Se describen otros cursos alternativos y se destaca la importancia de la perspectiva integradora del diseño de agentes inteligentes en la visión global de la asignatura. Se proponen diversas aproximaciones a los trabajos de laboratorio intentando satisfacer las restricciones de créditos y formación del estudiante en los distintos paradigmas de programación

Relevance-based language modelling for recommender systems

This is the author’s version of a work that was accepted for publication in Journal Information Processing and Management: an International Journal. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal Information Processing and Management: an International Journal, 49, 4, (2013) DOI: 10.1016/j.ipm.2013.03.001Relevance-Based Language Models, commonly known as Relevance Models, are successful approaches to explicitly introduce the concept of relevance in the statistical Language Modelling framework of Information Retrieval. These models achieve state-of-the-art retrieval performance in the pseudo relevance feedback task. On the other hand, the field of recommender systems is a fertile research area where users are provided with personalised recommendations in several applications. In this paper, we propose an adaptation of the Relevance Modelling framework to effectively suggest recommendations to a user. We also propose a probabilistic clustering technique to perform the neighbour selection process as a way to achieve a better approximation of the set of relevant items in the pseudo relevance feedback process. These techniques, although well known in the Information Retrieval field, have not been applied yet to recommender systems, and, as the empirical evaluation results show, both proposals outperform individually several baseline methods. Furthermore, by combining both approaches even larger effectiveness improvements are achieved.This work was funded by Secretaría de Estado de Investigación, Desarrollo e Innovación from the Spanish Government under Projects TIN2012-33867 and TIN2011-28538-C02

Priors for Diversity and Novelty on Neural Recommender Systems

[Abstract] PRIN is a neural based recommendation method that allows the incorporation of item prior information into the recommendation process. In this work we study how the system behaves in terms of novelty and diversity under different configurations of item prior probability estimations. Our results show the versatility of the framework and how its behavior can be adapted to the desired properties, whether accuracy is preferred or diversity and novelty are the desired properties, or how a balance can be achieved with the proper selection of prior estimations.Ministerio de Ciencia, Innovación y Universidades; RTI2018-093336-B-C22Xunta de Galicia; GPC ED431B 2019/03Xunta de Galicia; ED431G/01Ministerio de Ciencia, Innovación y Universidades; FPU17/03210Ministerio de Ciencia, Innovación y Universidades; FPU014/0172

Building High-Quality Datasets for Information Retrieval Evaluation at a Reduced Cost

[Abstract] Information Retrieval is not any more exclusively about document ranking. Continuously new tasks are proposed on this and sibling fields. With this proliferation of tasks, it becomes crucial to have a cheap way of constructing test collections to evaluate the new developments. Building test collections is time and resource consuming: it requires time to obtain the documents, to define the user needs and it requires the assessors to judge a lot of documents. To reduce the latest, pooling strategies aim to decrease the assessment effort by presenting to the assessors a sample of documents in the corpus with the maximum number of relevant documents in it. In this paper, we propose the preliminary design of different techniques to easily and cheapily build high-quality test collections without the need of having participants systems.Ministerio de Ciencia, Innovación y Universidades; RTI2018-093336-B-C22Xunta de Galicia; GPC ED431B 2019/03Xunta de Galicia; ED431G/0

When to stop making relevance judgments? A study of stopping methods for building information retrieval test collections

This is the peer reviewed version of the following article: David E. Losada, Javier Parapar and Alvaro Barreiro (2019) When to Stop Making Relevance Judgments? A Study of Stopping Methods for Building Information Retrieval Test Collections. Journal of the Association for Information Science and Technology, 70 (1), 49-60, which has been published in final form at https://doi.org/10.1002/asi.24077. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsIn information retrieval evaluation, pooling is a well‐known technique to extract a sample of documents to be assessed for relevance. Given the pooled documents, a number of studies have proposed different prioritization methods to adjudicate documents for judgment. These methods follow different strategies to reduce the assessment effort. However, there is no clear guidance on how many relevance judgments are required for creating a reliable test collection. In this article we investigate and further develop methods to determine when to stop making relevance judgments. We propose a highly diversified set of stopping methods and provide a comprehensive analysis of the usefulness of the resulting test collections. Some of the stopping methods introduced here combine innovative estimates of recall with time series models used in Financial Trading. Experimental results on several representative collections show that some stopping methods can reduce up to 95% of the assessment effort and still produce a robust test collection. We demonstrate that the reduced set of judgments can be reliably employed to compare search systems using disparate effectiveness metrics such as Average Precision, NDCG, P@100, and Rank Biased Precision. With all these measures, the correlations found between full pool rankings and reduced pool rankings is very highThis work received financial support from the (i) “Ministerio de Economía y Competitividad” of the Government of Spain and FEDER Funds under the researchproject TIN2015-64282-R, (ii) Xunta de Galicia (project GPC 2016/035), and (iii) Xunta de Galicia “Consellería deCultura, Educación e Ordenación Universitaria” and theEuropean Regional Development Fund (ERDF) throughthe following 2016–2019 accreditations: ED431G/01(“Centro singular de investigación de Galicia”) andED431G/08S

Docencia en sistemas de acceso á información: detección de plaxios, emprego de tecnoloxías avanzadas para desenvolvemento software e achegamento da experiencia na industria á aula

[Resumo] Este artigo presenta as actividades desenvolvidas polo grupo de innovación educativa en Sistemas de Acceso á Información durante o curso 2017/2018. Este grupo, con docencia na Facultade de Informática da Universidade da Coruña, realizou accións en tres liñas de actuación diferentes. A primeira delas, dirixida á mellora da calidade nos métodos de avaliación, consiste no emprego dun protocolo para a detección de plaxios en prácticas de programación. A segunda actividade pretende mellorar a empregabilidade do alumnado e consiste en utilizar unha metodoloxía de aprendizaxe baseada en proxectos xunto cunha serie de ferramentas avanzadas para desenvolvemento software, permitindo recrear a actividade que deberán levar a cabo cando se incorporen ao mundo laboral. Por último, e de cara a aumentar o coñecemento das alternativas profesionais do alumnado, organizáronse unha serie de seminarios e charlas impartidas por profesionais dunha empresa internacional, unha empresa local multidisciplinar e un investigador da contorna académica. A experiencia obtida das diferentes actividades foi satisfactoria e enriquecedora tanto para o alumnado como para o profesorado, que xa baralla melloras de cara aos vindeiros cursos académicos.[Abstract] This paper presents the activities performed by the educative innovation group in Information Access Systems during the academic year 2017/2018. This group, with teaching at the Faculty of Informatics of the University of A Coruña, carried out actions addressing three different topics. The first action was designed to improve the quality of the evaluation methods, and consisted in following a protocol for detecting plagiarism in programming exercises. The second activity aimed to improve the employability of the students and consisted in using a methodology based on project-based learning along with a series of advanced tools for software development, which recreated the activity that the students will carry out when they obtain their first job. Lastly, heading towards a better knowledge about the available professional alternatives, a series of seminars and talks were organized, which were performed by professionals from an international company, a local interdisciplinary company, and a researcher from an academic institution. The experience obtained from the different activities was satisfactory for both students and teachers, who are already considering improvements for the next academic year

Compare statistical significance tests for information retrieval evaluation

Preprint of our Journal of the Association for Information Science and Technology (JASIST) paper[Abstract] Statistical significance tests can provide evidence that the observed difference in performance between two methods is not due to chance. In Information Retrieval, some studies have examined the validity and suitability of such tests for comparing search systems.We argue here that current methods for assessing the reliability of statistical tests suffer from some methodological weaknesses, and we propose a novel way to study significance tests for retrieval evaluation. Using Score Distributions, we model the output of multiple search systems, produce simulated search results from such models, and compare them using various significance tests. A key strength of this approach is that we assess statistical tests under perfect knowledge about the truth or falseness of the null hypothesis. This new method for studying the power of significance tests in Information Retrieval evaluation is formal and innovative. Following this type of analysis, we found that both the sign test and Wilcoxon signed test have more power than the permutation test and the t-test. The sign test and Wilcoxon signed test also have a good behavior in terms of type I errors. The bootstrap test shows few type I errors, but it has less power than the other methods tested.Ministerio de Econom´ıa y Competitividad; TIN2015-64282-RXunta de Galicia; GPC 2016/035Xunta de Galicia; ED431G/01Xunta de Galicia; ED431G/0

Analisis del desplazamiento de la carga en vendimiadoras mediante el metodo de los elementos discretos

El pesado dinámico de las tolvas en una vendimiadora se ve afectado por diversas fuentes de variación. Una de ellas es el desplazamiento de la carga en su interior, debido principalmente a las inclinaciones del terreno a las que está expuesta la máquina. Este trabajo se ha realizado para cuantificar cómo se ve afectada la señal de la célula de carga en función de las inclinaciones de la máquina. El trabajo se ha dividido en dos partes: pruebas experimentales y modelización. La primera parte ha consistido en la realización de pruebas de laboratorio en las que la máquina vendimiadora, equipada con los correspondientes sensores y utilizando esferas de hidrogel como material para llenar la tolvas, fue sometida a distintas inclinaciones. En la segunda parte del trabajo se ha desarrollado un modelo de elementos discretos para simular el comportamiento de las esferas en el interior de la tolva y su efecto sobre la distribución de la carga. En un primer análisis de los datos se ha concluido que inclinaciones del terreno inferiores a 5° tendrían un efecto mínimo sobre el desplazamiento de la carga, y en consecuencia sobre la señal de la célula de carg

Using description logics to integrate fishers' ecological knowledge in the research of artisanal fisheries

[Abstract] The aim of this paper is to show the role that Knowledge Representation can play in the research of artisanal fisheries. In particular we concentrate on the epistemological and technological adequacy of implementations of Description Logics to represent fishers’ ecological knowledge, so contributing to address some open methodological questions about its collection and us