Now showing items 21-40 of 535

    • 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 ...
    • Utilising knowledge graph embeddings for data-to-text generation 

      Pasricha, Nivranshu; Arcan, Mihael; Buitelaar, Paul (Association for Computational Linguistics, 2020-12-18)
      Data-to-text generation has recently seen a move away from modular and pipeline architectures towards end-to-end architectures based on neural networks. In this work, we employ knowledge graph embeddings and explore their ...
    • NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation 

      Pasricha, Nivranshu; Arcan, Mihael; Buitelaar, Paul (Association for Computational Linguistics, 2020-12-18)
      This paper describes the system submitted by NUIG-DSI to the WebNLG+ challenge 2020 in the RDF-to-text generation task for the English language. For this challenge, we leverage transfer learning by adopting the T5 model ...
    • Uncovering semantic bias in neural network models using a knowledge graph 

      Nikolov, Andriy; d'Aquin, Mathieu (ACM, 2020-10-19)
      While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not ...
    • 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 ...
    • Synergy between embedding and protein functional association networks for drug label prediction using harmonic function 

      Timilsina, Mohan; Mc Kernan, Declan Patrick; Yang, Haixuan; d’Aquin, Mathieu (ACM and IEEE, 2020-10-16)
      Semi-Supervised Learning (SSL) is an approach to machine learning that makes use of unlabeled data for training with a small amount of labeled data. In the context of molecular biology and pharmacology, one can take advantage ...
    • Smart speaker design and implementation with biometric authentication and advanced voice interaction capability 

      Sudharsan, Bharath; Corcoran, Peter; Ali, Muhammad Intizar (CEUR-WS.org, 2019-12-05)
      Advancements in semiconductor technology have reduced dimensions and cost while improving the performance and capacity of chipsets. In addition, advancement in the AI frameworks and libraries brings possibilities to ...
    • Unsupervised method to analyze playing styles of EPL teams using ball possession-position data 

      Verma, Pranav; Sudharsan, Bharath; Chakravarthi, Bharathi Raja; O'Riordan, Colm; Hill, Seamus (IEEE, 2020-03-06)
      In the English Premier League (EPL) matches, a network of advanced systems gathers sports data in real-time to build a possession-position dataset. In this work, data fields from the sophisticated raw possession-position ...
    • NUIG-Panlingua-KMI Hindi-Marathi MT Systems for Similar Language Translation Task @ WMT 2020 

      Ojha, Atul Kr.; Rani, Priya; Bansal, Akanksha; Chakravarthi, Bharathi Raja; Kumar, Ritesh; McCrae, John P. (Association for Computational Linguistics, 2020-11-19)
      NUIG-Panlingua-KMI submission to WMT 2020 seeks to push the state-of-the-art in the Similar language translation task for the Hindi ↔ Marathi language pair. As part of these efforts, we conducted a series of experiments to ...
    • Findings of the LoResMT 2020 shared task on zero-shot for low-resource languages 

      Ojha, Atul Kr.; Malykh, Valentin; Karakanta, Alina; Liu, Chao-Hong (Association for Computational Linguistics, 2020-12-04)
      This paper presents the findings of the LoResMT 2020 Shared Task on zero-shot translation for low resource languages. This task was organised as part of the 3rd Workshop on Technologies for MT of Low Resource Languages ...
    • Towards automatic linking of lexicographic data: the case of a historical and a modern Danish dictionary 

      Ahmadi, Sina; Nimb, Sanni; McCrae, John P.; Sørensen, Nicolai H. (European Association for Lexicography, 2020)
      Given the diversity of lexical-semantic resources, particularly dictionaries, integrating such resources by aligning various types of information is an important task, both in e-lexicography and natural language processing. ...
    • Automatic morphological analysis and interlinking of historical Irish cognate verb forms 

      Fransen, Theodorus (De Gruyter Mouton, 2020)
      The main aim of the author’s research project is to use computational approaches to gain more insight into the historical development of Irish verbs. One of the objectives is to investigate how a link between the electronic ...
    • Enrichment of blockchain transaction management with semantic triples 

      Yapa Bandara, Kosala; Thakur, Subhasis; Breslin, John (National University of Ireland Galway, 2020-11-02)
      Abstract—Enterprise business transactions have both public and private information; hence blockchain adaptation to an enterprise business application needs current blockchain platforms to support both public and private ...
    • Renewable energy integration through coalition formation for P2P energy trading 

      Yapa Bandara, Kosala; Thakur, Subhasis; Breslin, John (National University of Ireland Galway, 2020-10-09)
      Renewable energy sources are highly unreliable; hence prosumers connected to renewable energy sources find unreliable energy surplus and demands which should be managed frequently within neighbourhoods. Peer-to-peer(P2P) ...
    • Cardamom: Comparative deep models for minority and historical languages 

      McCrae, John Philip; Fransen, Theodorus (Language Technologies for All (LT4All), 2019-12-05)
      This paper gives an overview of the Cardamom project, which aims to close the resource gap for minority and under-resourced languages by means of deep-learning-based natural language processing (NLP) and exploiting ...
    • A sentiment analysis dataset for code-mixed Malayalam-English 

      Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul; Sherly, Elizabeth; McCrae, John P. (European Language Resources Association (ELRA), 2020-05-11)
      There is an increasing demand for sentiment analysis of text from social media which are mostly code-mixed. Systems trained on monolingual data fail for code-mixed data due to the complexity of mixing at different levels ...
    • 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 ...
    • Is trust between AI institutions and the public “morally rotten?” 

      Carter, Sarah (Machine Ethics Research Group, School of Computer Science, University College Dublin, 2020)
      Developing artificial Intelligence (AI) technology has become a business of power. AI innovation is increasingly centralized in a few large companies – mainly, Google, Facebook, and Apple.1 Specialized data scientists - ...
    • A survey of current datasets for code-switching research 

      Jose, Navya; Chakravarthi, Bharathi Raja; Suryawanshi, Shardul; Sherly, Elizabeth; McCrae, John P. (IEEE, 2020-03-06)
      Code switching is a prevalent phenomenon in the multilingual community and social media interaction. In the past ten years, we have witnessed an explosion of code switched data in the social media that brings together ...
    • 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, ...