Listar Information Retrieval Lab (IRlab) por título
Mostrando ítems 11-30 de 37
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Delving into the Depths: Evaluating Depression Severity through BDI-biased Summaries
(Association for Computational Linguistics, 2024-03)[Abstract]: Depression is a global concern suffered by millions of people, significantly impacting their thoughts and behavior. Over the years, heightened awareness, spurred by health campaigns and other initiatives, has ... -
Designing an Open Source Virtual Assistant
(MDPI AG, 2020-08-21)[Abstract] A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most ... -
Equilibrium graphs
(Springer, 2019)[Abstract]: In this paper we present an extension of Peirce’s existential graphs to provide a diagrammatic representation of expressions in Quantified Equilibrium Logic (QEL). Using this formalisation, logical connectives ... -
eRisk 2020: autolesiones y desafíos de la depresión
(Springer, 2020-04-08)[Abstract] This paper describes eRisk, the CLEF lab on early risk prediction on the Internet. eRisk started in 2017 as an attempt to set the experimental foundations of early risk detection. Over the last three editions ... -
Evolving Cellular Automata Schemes for Protein Folding Modeling Using the Rosetta Atomic Representation
(Springer, 2022)[Abstract] Protein folding is the dynamic process by which a protein folds into its final native structure. This is different to the traditional problem of the prediction of the final protein structure, since it requires ... -
Experimental Analysis of the Relevance of Features and Effects on Gender Classification Models for Social Media Author Profiling
(SCITEPRESS, 2021)[Abstract] Automatic user profiling from social networks has become a popular task due to its commercial applications (targeted advertising, market studies...). Automatic profiling models infer demographic characteristics of ... -
Forgetting Auxiliary Atoms in Forks
(Elsevier Ltd, 2019)[Abstract]: In this work we tackle the problem of checking strong equivalence of logic programs that may contain local auxiliary atoms, to be removed from their stable models and to be forbidden in any external context. ... -
Hybrid Intelligence Strategies for Identifying, Classifying and Analyzing Political Bots
(MDPI, 2021)[Abstract] Political bots, through astroturfing and other strategies, have become important players in recent elections in several countries. This study aims to provide researchers and the citizenry with the necessary ... -
Keyword Embeddings for Query Suggestion
(Springer, Cham, 2023-04)[Abstract]: Nowadays, search engine users commonly rely on query suggestions to improve their initial inputs. Current systems are very good at recommending lexical adaptations or spelling corrections to users’ queries. ... -
Linear-Time Temporal Answer Set Programming
(Cambridge University Press, 2023)[Abstract]: In this survey, we present an overview on (Modal) Temporal Logic Programming in view of its application to Knowledge Representation and Declarative Problem Solving. The syntax of this extension of logic programs ... -
M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines
(Elsevier B.V., 2020-11)[Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ... -
Machine learning predicts 3D printing performance of over 900 drug delivery systems
(Elsevier B.V., 2021-09)[Abstract]: Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy ... -
Minish HAT: A Tool for the Minimization of Here-and-There Logic Programs and Theories in Answer Set Programming
(M D P I AG, 2019-07-31)[Abstract] When it comes to the writing of a new logic program or theory, it is of great importance to obtain a concise and minimal representation, for simplicity and ease of interpretation reasons. There are already a few ... -
Model Explanation via Support Graphs
(Cambridge Univeristy Press, 2024-02)[Absctract]: In this note, we introduce the notion of support graph to define explanations for any model of a logic program. An explanation is an acyclic support graph that, for each true atom in the model, induces a proof ... -
Multiple-Choice Question Answering Models for Automatic Depression Severity Estimation
(MDPI, 2021)[Abstract] Depression is one of the most prevalent mental health diseases. Although there are effective treatments, the main problem relies on providing early and effective risk detection. Medical experts use self-reporting ... -
Niching methods integrated with a differential evolution memetic algorithm for protein structure prediction
(Elsevier, 2022-06)[Abstract]: A memetic version between an evolutionary algorithm (differential evolution) and the local search provided by protein fragment replacements was defined for protein structure prediction. In this problem, it is ... -
Novel and Diverse Recommendations by Leveraging Linear Models with User and Item Embeddings
(Springer, 2020-04-08)[Abstract] Nowadays, item recommendation is an increasing concern for many companies. Users tend to be more reactive than proactive for solving information needs. Recommendation accuracy became the most studied aspect of ... -
On the semantics of hybrid ASP systems based on Clingo
(MDPI, 2023-03)[Abstract]: Over the last decades, the development of Answer Set Programming (ASP) has brought about an expressive modeling language powered by highly performant systems. At the same time, it gets more and more difficult ... -
Predicting pharmaceutical inkjet printing outcomes using machine learning
(Elsevier B.V., 2023)[Abstract]: Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex ... -
Priors for Diversity and Novelty on Neural Recommender Systems
(M D P I AG, 2019-07-31)[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 ...
