Browsing by Author "Ronzano, Francesco"

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  • A multi-layered annotated corpus of scientific papers
    Fisas Elizalde, Beatriz; Ronzano, Francesco; Saggion, Horacio (ELRA (European Language Resources Association), 2016)
    Scientific literature records the research process with a standardized structure and provides the clues to track the progress in a scientific field. Understanding its internal structure and content is of paramount importance ...
  • An empirical assessment of citation information in scientific summarization
    Saggion, Horacio; Ronzano, Francesco (Springer, 2016)
    Considering the recent substantial growth of the publication rate of scientific results, nowadays the availability of effective and automated techniques to summarize scientific articles is of utmost importance. In this ...
  • Clinical-based and expert selection of terms related to depression for twitter streaming and language analysis
    Leis Machín, Angela 1974-; Mayer, Miguel Ángel, 1960-; Ronzano, Francesco; Torrens, Marta; Castillo, Claudio; Furlong, Laura I., 1971-; Sanz, Ferran (IOS Press, 2020)
    People use language to express their thoughts and feelings, unveiling important aspects of their psychological traits and social interactions. Although there are several studies describing methodologies to create a collection ...
  • DEFEXT: a semi supervised definition extraction tool
    Espinosa-Anke, Luis; Carlini, Roberto; Saggion, Horacio; Ronzano, Francesco (European Language Resources Association, 2016)
    We present DEFEXT, an easy to use semi supervised Definition Extraction Tool. DEFEXT is designed to extract from a target corpus those textual fragments where a term is explicitly mentioned together with its core features, ...
  • Detecting signs of depression in tweets in spanish: behavioral and linguistic analysis
    Leis Machín, Angela 1974-; Ronzano, Francesco; Mayer, Miguel Ángel, 1960-; Furlong, Laura I., 1971-; Sanz, Ferran (JMIR Publications, 2019)
    Background: Mental disorders have become a major concern in public health, and they are one of the main causes of the overall disease burden worldwide. Social media platforms allow us to observe the activities, thoughts, ...
  • EmoTwi50 [research data]
    Barbieri, Francesco; Ronzano, Francesco; Saggion, Horacio (Universitat Pompeu Fabra, 2016)
  • Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study
    Leis Machín, Angela 1974-; Ronzano, Francesco; Mayer, Miguel Ángel, 1960-; Furlong, Laura I., 1971-; Sanz, Ferran (JMIR Publications, 2020)
    Background: Depressive disorders are the most common mental illnesses, and they constitute the leading cause of disability worldwide. Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed drugs ...
  • Exploring the association of cancer and depression in electronic health records: combining encoded diagnosis and mining free-text clinical notes
    Leis Machín, Angela 1974-; Casadevall Aguilar, David; Albanell Mestres, Joan; Posso, Margarita; Macià Guilà, Francesc Assís; Castells, Xavier; Ramírez Anguita, Juan Manuel; Martínez Roldán, Jordi; Furlong, Laura I., 1971-; Sanz, Ferran; Ronzano, Francesco; Mayer, Miguel Ángel, 1960- (JMIR Publications, 2022)
    Background: A cancer diagnosis is a source of psychological and emotional stress, which are often maintained for sustained periods of time that may lead to depressive disorders. Depression is one of the most common ...
  • Genomic and proteomic biomarker landscape in clinical trials
    Piñero González, Janet, 1977-; Rodriguez Fraga, Pablo S.; Valls-Margarit, Jordi; Ronzano, Francesco; Accuosto, Pablo; Lambea Jane, Ricard; Sanz, Ferran; Furlong, Laura I., 1971- (Elsevier, 2023)
    The use of molecular biomarkers to support disease diagnosis, monitor its progression, and guide drug treatment has gained traction in the last decades. While only a dozen biomarkers have been approved for their exploitation ...
  • How cosmopolitan are emojis? Exploring emojis usage and meaning over different languages with distributional semantics
    Barbieri, Francesco; Kruszewski, German; Ronzano, Francesco; Saggion, Horacio (ACM Association for Computer Machinery, 2016)
    Choosing the right emoji to visually complement or con- dense the meaning of a message has become part of our daily life. Emojis are pictures, which are naturally combined with plain text, thus creating a new form of ...
  • Hypernym extraction: combining machine-learning and dependency grammar
    Espinosa-Anke, Luis; Ronzano, Francesco; Saggion, Horacio (Springer, 2015)
    Hypernym extraction is a crucial task for semantically motivated NLP tasks such as taxonomy and ontology learning, textual entailment or paraphrase identification. In this paper, we describe an approach to hypernym extraction ...
  • Knowledge extraction and modeling from scientific publications
    Ronzano, Francesco; Saggion, Horacio (Springer, 2016)
    During the last decade the amount of scientific articles available online has substantially grown in parallel with the adoption of the Open Access publishing model. Nowadays researchers, as well as any other interested ...
  • Making sense of massive amounts of scientific publications: the scientific knowledge miner project
    Ronzano, Francesco; Freire, Ana; Sáez-Trumper, Diego; Saggion, Horacio (CEUR Workshop Proceedings, 2016)
    The World Wide Web has become the hugest repository ever for scientific publications and it continues to increase at an unprecedented rate. Nevertheless, this information overload makes the exploration of this content a ...
  • Multi-level mining and visualization of scientific text collections
    Accuosto, Pablo; Ronzano, Francesco; Ferrés, Daniel; Saggion, Horacio (ACM Association for Computer Machinery, 2017)
    We present a system to mine and visualize collections of scientific documents by semantically browsing information extracted from single publications or aggregated throughout corpora of articles. The text mining tool ...
  • Multimodal emoji prediction
    Barbieri, Francesco; Ballesteros, Miguel; Ronzano, Francesco; Saggion, Horacio (ACL (Association for Computational Linguistics), 2018)
    Emojis are small images that are commonly included in social media text messages. The combination of visual and textual content in the same message builds up a modern way of communication, that automatic systems are not ...
  • MultiScien: a bi-lingual natural language processing system for mining and enrichment of scientific collections
    Saggion, Horacio; Ronzano, Francesco; Accuosto, Pablo; Ferrés, Daniel (CEUR Workshop Proceedings, 2017)
    In the current online Open Science context, scientific datasets and tools for deep text analysis, visualization and exploitation play a major role.We present a system for deep analysis and annotation of scientific text ...
  • PDFdigest: an adaptable layout-aware PDF-to-XML textual content extractor for scientific articles
    Ferrés, Daniel; Saggion, Horacio; Ronzano, Francesco; Bravo Serrano, Àlex, 1984- (ACL (Association for Computational Linguistics), 2018)
    The availability of automated approaches and tools to extract structured textual content from PDF articles is essential to enable scientific text mining. This paper describes and evaluates the PDFdigest tool, a PDF-to-XML ...
  • SemEval 2018 Task 2: multilingual emoji prediction
    Barbieri, Francesco; Camacho-Collados, Jose; Ronzano, Francesco; Espinosa-Anke, Luis; Ballesteros, Miguel; Basile, Valerio; Patti, Viviana; Saggion, Horacio (ACL (Association for Computational Linguistics), 2018)
    This paper describes the results of the first shared task on Multilingual Emoji Prediction, organized as part of SemEval 2018. Given the text of a tweet, the task consists of predicting the most likely emoji to be used ...
  • TALN at SemEval-2016 Task 11: modelling complex words by contextual, lexical and semantic features
    Ronzano, Francesco; AbuRa'ed, Ahmed Ghassan Tawfiq; Espinosa-Anke, Luis; Saggion, Horacio (ACL (Association for Computational Linguistics), 2016)
    This paper presents the participation of the TALN team in the Complex Word Identification Task of SemEval-2016 (Task 11). The purpose of the task was to determine if a word in a given sentence can be judged as complex or ...
  • TALN-UPF: taxonomy learning exploiting CRF-based hypernym extraction on encyclopedic definitions
    Espinosa-Anke, Luis; Saggion, Horacio; Ronzano, Francesco (ACL (Association for Computational Linguistics), 2015)
    This paper describes the system submitted by the TALN-UPF team to SEMEVAL Task 17 (Taxonomy Extraction Evaluation). We present a method for automatically learning a taxonomy from a flat terminology, which benefits from a ...