Browsing Data Science Institute by Author "http://dx.doi.org/10.13039/501100008530"

Now showing items 1-20 of 39

    • 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 ...

    • 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 ...

    • 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 ...

    • 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, ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Discovering protein drug targets using knowledge graph embeddings 

      Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Oxford University Press, 2019-08-01)
      Motivation Computational approaches for predicting drug-target interactions (DTIs) can provide valuable insights into the drug mechanism of action. DTI predictions can help to quickly identify new promising (on-target) ...

    • Edge2Guard: Botnet attacks detecting offline models for resource-constrained IoT devices 

      Sudharsan, Bharath; Sundaram, Dineshkumar; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (National University of Ireland Galway, 2021-03-22)
      In today's IoT smart environments, dozens of MCU-based connected device types exist such as HVAC controllers, smart meters, smoke detectors, etc. The security conditions for these essential IoT devices remain unsatisfactory ...

    • Edge2Train: A framework to train machine learning models (SVMs) on resource-constrained IoT edge devices 

      Sudharsan, Bharath; Breslin, John G.; Ali, Muhammad Intizar (Association for Computing Machinery (ACM), 2020-10-06)
      In recent years, ML (Machine Learning) models that have been trained in data centers can often be deployed for use on edge devices. When the model deployed on these devices encounters unseen data patterns, it will either ...

    • The ELEXIS interface for interoperable lexical resources 

      McCrae, John P.; Tiberius, Carole; Khan, Anas Fahad; Kernerman, Ilan; Declerck, Thierry; Krek, Simon; Monachini, Monica; Ahmadi, Sina (eLex 2019, 2019-10-01)
      ELEXIS is a project that aims to create a European network of lexical resources, and one of the key challenges for this is the development of an interoperable interface for different lexical resources so that further ...

    • Enabling machine learning on the edge using SRAM conserving efficient neural networks execution approach 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (National University of Ireland Galway, 2021-09-13)
      Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the ...

    • Enhancing multiple-choice question answering with causal knowledge 

      Dalal, Dhairya; Arcan, Mihael; Buitelaar, Paul (Association for Computational Linguistics, 2021-06-10)
      The task of causal question answering aims to reason about causes and effects over a provided real or hypothetical premise. Recent approaches have converged on using transformer-based language models to solve question ...

    • Extending largeRDFBench for multi-source data at scale for SPARQL endpoint federation 

      Hasnain, Ali; Saleem, Muhammad; Ngomo, Axel-Cyrille Ngonga; Rebholz-Schuhmann, Dietrich (IOS Press, 2018)
      Querying the Web of Data is highly motivated by the use of federation approaches mainly SPARQL query federation when the data is available through endpoints. Different benchmarks have been proposed to exploit the full ...

    • Inferring translation candidates for multilingual dictionary generation with multi-way neural machine translation 

      Arcan, Mihael; Torregrosa, Daniel; Ahmadi, Sina; McCrae, John P. (National University of Ireland, Galway, 2019-05-20)
      In the widely-connected digital world, multilingual lexical resources are one of the most important resources, for natural language processing applications, including information retrieval, question answering or knowledge ...

    • Leveraging rule-based machine translation knowledge for under-resourced neural machine translation models 

      Torregrosa, Daniel; Pasricha, Nivranshu; Chakravarth, Bharathi Raja; Masoud, Maraim; Alonso, Juan; Casas, Noe; Arcan, Mihael (NUI Galway, 2019-08-19)
      Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate from source to target language. While this approach grants total ...

    • Linked data cased multi-omics integration and visualization for cancer decision networks 

      Jha, Alokkumar; Khan, Yasar; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (Springer Verlag, 2018-12-30)
      Visualization of Gene Expression (GE) is a challenging task since the number of genes and their associations are difficult to predict in various set of biological studies. GE could be used to understand tissue-gene-protein ...

    • Multilingual multimodal machine translation for Dravidian languages utilizing phonetic transcription 

      Chakravarthi, Bharathi Raja; Priyadharshini, Ruba; Stearns, Bernardo; Jayapal, Arun; Sridevy, S.; Arcan, Mihael; Zarrouk, Manel; McCrae, John P. (European Association for Machine Translation, 2019-08-19)
      Multimodal machine translation is the task of translating from a source text into the target language using information from other modalities. Existing multimodal datasets have been restricted to only highly resourced ...