Browsing Data Science Institute by Author "http://dx.doi.org/10.13039/501100001602"

Now showing items 1-20 of 113

    • AFEL-Analytics for Everyday Learning 

      d’Aquin, Mathieu; Kowald, Dominik; Fessl, Angela; Lex, Elisabeth; Thalmann, Stefan (ACM, 2018-04-23)
      The goal of AFEL is to develop, pilot and evaluate methods and applications, which advance informal/collective learning as it surfaces implicitly in online social environments. The project is following a multi-disciplinary, ...

    • Asistent -- a machine translation system for Slovene, Serbian and Croatian 

      Arcan, Mihael; Popovic, Maja; Buitelaar, Paul (University of Ljubljana, 2016-09-29)
      The META-NET research on language technologies in 2012 showed a weak support on tools for crossing the language barrier for many European languages, including the south Slavic languages. Therefore, we describe a statistical ...

    • Assessing FAIR data principles against the 5-Star open data principles 

      Hasnain, Ali; Rebholz-Schuhmann, Dietrich (Springer Verlag, 2018-08-02)
      Access to biomedical data is increasingly important to enable data driven science in the research community. The Linked Open Data (LOD) principles (by Tim Berner-Lee) have been suggested to judge the quality of data by its ...

    • Automatic enrichment of terminological resources: the IATE RDF example 

      Arcan, Mihael; Montiel-Ponsoda, Elena; McCrae, John P.; Buitelaar, Paul (European Language Resources Association, 2018-05-07)
      Terminological resources have proven necessary in many organizations and institutions to ensure communication between experts. However, the maintenance of these resources is a very time-consuming and expensive process. ...

    • Automatic taxonomy generation: a use-case in the legal domain 

      Robin, Cécile; O'Neill, James; Buitelaar, Paul (LTC'17, 8th Language & Technology Conference, 2017-11-17)
      A key challenge in the legal domain is the adaptation and representation of the legal knowledge expressed through texts, in order for legal practitioners and researchers to access this information more easily and faster ...

    • Back-translation approach for code-switching machine translation: A case study 

      Masoud, Maraim; Torregrosa, Daniel; Buitelaar, Paul; Arčan, Mihael (AICS2019, 2019-12-05)
      Recently, machine translation has demonstrated significant progress in terms of translation quality. However, most of the research has focused on translating with pure monolingual texts in the source and the target side ...

    • BEARS: Towards an evaluation framework for bandit-based interactive recommender systems 

      Barraza-Urbina, Andrea; Koutrika, Georgia; d'Aquin, Mathieu,; Hayes, Conor (NUI Galway, 2018-10-06)
      Recommender Systems (RS) deployed in fast-paced dynamic scenarios must quickly learn to adapt in response to user evaluative feedback. In these settings, the RS faces an online learning problem where each decision should ...

    • Biological applications of knowledge graph embedding models 

      Mohamed, Sameh K.; Nounu, Aayah; Nováček, Vít (Oxford University Press (OUP), 2020-02-17)
      Complex biological systems are traditionally modelled as graphs of interconnected biological entities. These graphs, i.e. biological knowledge graphs, are then processed using graph exploratory approaches to perform different ...

    • CoFiF: A corpus of financial reports in French language 

      Ahmadi, Sina; Daudert, Tobias (NUI Galway, 2019-08-12)
      In an era when machine learning and artificial intelligence have huge momentum, the data demand to train and test models is steadily growing. We introduce CoFiF, the first corpus comprising company reports in the French ...

    • The colloquial WordNet: Extending Princeton WordNet with neologisms 

      McCrae, John P.; Wood, Ian D.; HIcks, Amanda (Springer International Publishing, 2017-05-27)
      Princeton WordNet is one of the most important resources for natural language processing, but has not been updated for over ten years and is not suitable for analyzing the fast moving language as used on social media. We ...

    • A comparative study of different state-of-the-art hate speech detection methods in Hindi-English code-mixed data 

      Rani, Priya; Suryawanshi, Shardul; Goswami, Koustava; Chakravarthi, Bharathi Raja; Fransen, Theodorus; McCrae, John P. (European Language Resources Association (ELRA), 2020-05-11)
      Hate speech detection in social media communication has become one of the primary concerns to avoid conflicts and curb undesired activities. In an environment where multilingual speakers switch among multiple languages, ...

    • A comparison of emotion annotation approaches for text 

      Wood, Ian D.; McCrae, John P.; Andryushechkin, Vladimir; Buitelaar, Paul (MDPI, 2018-05-11)
      While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of a more nuanced affect has received less attention: there ...

    • A comparison of emotion annotation schemes and a new annotated data set 

      Wood, Ian D.; McCrae, John P.; Andryushechkin, Vladimir; Buitelaar, Paul (European Languages Resources Association (ELRA), 2018-05-07)
      While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of more nuanced affect has received less attention, and ...

    • A comparison of statistical and neural machine translation for Slovene, Serbian and Croatian 

      Arcan, Mihael (Language Technologies and Digital Humanities 2018, 2018-09-20)
      In this paper we present a comparison of translation quality using of Statistical Machine Translation (SMT) and Neural Machine Translation (NMT), considering translation directions between English, Slovene, Serbian and ...

    • Corpus creation for sentiment analysis in code-mixed Tamil-English text 

      Chakravarthi, Bharathi Raja; Muralidaran, Vigneshwaran; Priyadharshini, Ruba; McCrae, John P. (European Language Resources Association (ELRA), 2020-05-11)
      Understanding the sentiment of a comment from a video or an image is an essential task in many applications. Sentiment analysis of a text can be useful for various decision-making processes. One such application is to ...

    • Cross-lingual sentence embedding using multi-task learning 

      Goswami, Koustava; Dutta, Sourav; Assem, Haytham; Fransen, Theodorus; McCrae, John P. (Association for Computational Linguistics, 2021-11-07)
      Multilingual sentence embeddings capture rich semantic information not only for measuring similarity between texts but also for catering to a broad range of downstream cross-lingual NLP tasks. State-of-the-art multilingual ...

    • CURED4NLG: A dataset for table-to-text generation 

      Pasricha, Nivranshu; Arcan, Mihael; Buitelaar, Paul (University of Galway, 2023)
      We introduce CURED4NLG, a dataset for the task of table-to-text generation focusing on the public health domain. The dataset consists of 280 pairs of tables and documents extracted from weekly epidemiological reports ...

    • The data ethics challenges of explainable AI and their knowledge-based solutions 

      d'Aquin, Mathieu (IOS Press, 2020-05)
      Abstract. Explainable AI has recently gained momentum as an approach to overcome some of the more obvious ethical implications of the increasingly widespread application of AI (mostly machine learning). It is however not ...

    • A dataset for troll classification of Tamil memes 

      Chakravarthi, Bharathi Raja; Varma, Pranav; Arcan, Mihael; McCrae, John P.; Buitelaar, Paul; Shardul, Suryawanshi (European Language Resources Association (ELRA), 2020-05-11)
      Social media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people. This exchange is not free from offensive, trolling or malicious contents ...

    • Deep convolution neural network model to predict relapse in breast cancer 

      Jha, Alokkumar; Verma, Ghanshyam; Khan, Yasar; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (IEEE, 2018-12-17)
      A mishap in anti-cancer drug distribution is critical in breast cancer patients due to poor prediction model to identify the treatment regime in ER+ve and ER-ve (Estrogen Receptor (ER)) patients. The traditional method for ...