• 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. ...

• 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 ...

• Multiple-Choice Question Answering Models for Automatic Depression Severity Estimation 

  Gabín, Jorge; Pérez, Anxo; Parapar, Javier (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 ...

• 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 ...

• 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 ...

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