Listar Information Retrieval Lab (IRlab) por título

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    • A Polynomial Reduction of Forks Into Logic Programs 

      Aguado, Felicidad; Cabalar, Pedro; Fandiño, Jorge; Pearce, David; Pérez, Gilberto; Vidal, Concepción (Elsevier, 2022)
      [Abstract] In this research note we present additional results for an earlier published paper [1]. There, we studied the problem of projective strong equivalence (PSE) of logic programs, that is, checking whether two logic ...

    • A System for Explainable Answer Set Programming 

      Cabalar, Pedro; Fandinno, Jorge; Muñiz, Brais (Open Publishing Association, 2020-09-19)
      [Abstract] We present xclingo, a tool for generating explanations from ASP programs annotated with text and labels. These annotations allow tracing the application of rules or the atoms derived by them. The input of ...

    • Accelerating 3D printing of pharmaceutical products using machine learning 

      Ong, Jun Jie; Muñiz, Brais; Gaisford, Simon; Cabalar, Pedro; Basit, Abdul W; Pérez, Gilberto; Goyanes, Álvaro (Elsevier, 2022)
      [Abstract] Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy ...

    • ALBAYZIN 2018 spoken term detection evaluation: a multi-domain international evaluation in Spanish 

      Tejedor, Javier; Toledano, Doroteo T.; López-Otero, Paula; Docío-Fernández, Laura; Montalvo, Ana R.; Ramírez, José M.; Peñagarikano, Mikel; Rodríguez-Fuentes, Luis Javier (SpringerOpen, 2019-09-02)
      [Abstract] Search on speech (SoS) is a challenging area due to the huge amount of information stored in audio and video repositories. Spoken term detection (STD) is an SoS-related task aiming to retrieve data from a speech ...

    • aspBEEF: Explaining Predictions Through Optimal Clustering 

      Cabalar, Pedro; Martín, Rodrigo; Muñiz, Brais; Pérez, Gilberto (MDPI AG, 2020-08-28)
      [Abstract] In this paper we introduce aspBEEF, a tool for generating explanations for the outcome of an arbitrary machine learning classifier. This is done using Grover’s et al. framework known as Balanced English ...

    • Automatic depression score estimation with word embedding models 

      Pérez, Anxo; Parapar, Javier; Barreiro, Álvaro (Elsevier, 2022)
      [Abstract]: Depression is one of the most common mental health illnesses. The biggest obstacle lies in an efficient and early detection of the disorder. Self-report questionnaires are the instruments used by medical experts ...

    • Building Cultural Heritage Reference Collections from Social Media through Pooling Strategies: The Case of 2020’s Tensions Over Race and Heritage 

      Otero, David; Martín-Rodilla, Patricia; Parapar, Javier (2021)
      [Abstract] Social networks constitute a valuable source for documenting heritage constitution processes or obtaining a real-time snapshot of a cultural heritage research topic. Many heritage researchers use social networks ...

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

      Otero, David; Valcarce, Daniel; Parapar, Javier; Barreiro, Álvaro (M D P I AG, 2019-08-01)
      [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 ...

    • Comparing the Reasoning Capabilities of Equilibrium Theories and Answer Set Programs 

      Fandiño, Jorge; Pearce, David; Vidal, Concepción; Woltran, Stefan (MDPI, 2022)
      [Abstract] Answer Set Programming (ASP) is a well established logical approach in artificial intelligence that is widely used for knowledge representation and problem solving. Equilibrium logic extends answer set semantics ...

    • Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends 

      Górriz, Juan M.; Álvarez-Illán, I.; Álvarez-Marquina, Agustín; Arco, Juan Eloy; Atzmueller, Martin; Ballarini, F.; Barakova, Emilia; Bologna, Guido; Duro, Richard J. Richard J. xxx; Santos Reyes, José (Elsevier, 2023-12)
      [Abstract]: Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear ...

    • Designing an Open Source Virtual Assistant 

      Pérez, Anxo; López-Otero, Paula; Parapar, Javier (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 

      Cabalar, Pedro; Pérez Ramil, Carlos; Pérez, Gilberto (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 

      Losada, David E.; Crestani, Fabio; Parapar, Javier (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 

      Varela, Daniel; Santos Reyes, José (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 

      Piot, Paloma; Martín-Rodilla, Patricia; Parapar, Javier (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 

      Aguado, Felicidad; Cabalar, Pedro; Fandiño, Jorge; Pearce, David; Pérez, Gilberto; Vidal, Concepción (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 

      García Orosa, Berta; Gamallo, Pablo; Martín-Rodilla, Patricia; Martínez-Castaño, Rodrigo (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 

      Gabín, Jorge; Ares, M. Eduardo; Parapar, Javier (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 

      Aguado, Felicidad; Cabalar, Pedro; Diéguez Lodeiro, Martín; Pérez, Gilberto; Schaub, Torsten; Schuhmann, Anna; Vidal, Concepción (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 

      Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (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) ...