Recent Submissions

  • NUIG at TIAD 2021: Cross-lingual word embeddings for translation inference 

    Ahmadi, Sina; Ojha, Atul Kr.; Banerjee, Shubhanker; McCrae, John P. (2021-09-01)
    Inducing new translation pairs across dictionaries is an important task that facilitates processing and maintaining lexicographical data. This paper describes our submissions to the Translation Inference Across Dictionaries ...
  • Do city dashboards make sense? Conceptualising user experiences and challenges in using city dashboards. A case study 

    Vornhagen, Heike; Zarrouk, Manel; Davis, Brian; Young, Karen (Association for Computing Machinery (ACM), 2021-06-09)
    City dashboards present information about a city to a broad audience with some thought given as to how some of these audiences might understand the information. However, little research has looked at how ’citizens’ make ...
  • Understanding my city through dashboards. How hard can it be? 

    Vornhagen, Heike; Young, Karen; Zarrouk, Manel (International Federation for Information Processing (IFIP) and eJournal of eDemocracy and Open Government (JeDEM), 2019-09-02)
    This paper describes research into how current city dashboards support users' sensemaking processes. It uses criteria identified in previous research concerning visualisation and applies these to a number of city dashboards ...
  • Traffic prediction framework for OpenStreetMap using deep learning based complex event processing and open traffic cameras 

    Yadav, Piyush; Sarkar, Dipto; Salwala, Dhaval; Curry, Edward (Dagstuhl Research Online Publication Server (DROPS), 2020-09-25)
    Displaying near-real-time traffic information is a useful feature of digital navigation maps. However, most commercial providers rely on privacy-compromising measures such as deriving location information from cellphones ...
  • RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices 

    Sudharsan, Bharath; Breslin, John G.; Ali, Muhammad Intizar (Association for Computing Machinery (ACM), 2020-10-06)
    Microcontroller Units (MCUs) in edge devices are resource constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing machine ...
  • 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 ...
  • 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 ...
  • Ultra-fast machine learning classifier execution on IoT devices without SRAM consumption 

    Sudharsan, Bharath; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (Institute of Electrical and Electronics Engineers (IEEE), 2021-05-25)
    With the introduction of edge analytics, IoT devices are becoming smart and ready for AI applications. A few modern ML frameworks are focusing on the generation of small-size ML models (often in kBs) that can directly be ...
  • TinyML benchmark: Executing fully connected neural networks on commodity microcontrollers 

    Sudharsan, Bharath; Salerno, Simone; Nguyen, Duc-Duy; Yahya, Muhammad; Wahid, Abdul; Yadav, Piyush; Breslin, John G. (National University of Ireland Galway, 2021-06-20)
    Recent advancements in the field of ultra-low-power machine learning (TinyML) promises to unlock an entirely new class of edge applications. However, continued progress is restrained by the lack of benchmarking Machine ...
  • 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 ...
  • 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. ...
  • 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) ...
  • 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 term extraction approach to survey analysis in health care 

    Robin, Cécile; Isazad Mashinchi, Mona; Ahmadi Zeleti, Fatemeh; Ojo, Adegboyega; Buitelaar, Paul (European Language Resources Association, 2020-05)
    The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches ...
  • A multilingual evaluation dataset for monolingual word sense alignment 

    Ahmadi, Sina; McCrae, John P.; Nimb, Sanni; Khan, Fahad; Monachini, Monica; Pedersen, Bolette S.; Declerck, Thierry; Wissik, Tanja; Bellandi, Andrea; Pisani, Irene; Troelsgård, Thomas; Olsen, Sussi; Krek, Simon; Lipp, Veronika; Váradi, Tamás; Simon, László; Gyorffy, Andras; Tiberius, Carole; Schoonheim, Tanneke; Moshe, Yifat Ben; Rudich, Maya; Ahmad, Raya Abu; Lonke, Dorielle; Kovalenko, Kira; Langemets, Margit; Kallas, Jelena; Oksana, Dereza; Fransen, Theodorus; Cillessen, David; Lindemann, David; Alonso, Mikel; Salgado, Ana; Sancho, Jose Luis; Urena-Ruiz, Rafael-J.; Zamorano, Jordi Porta; Simov, Kiril; Osenova, Petya; Kancheva, Zara; Radev, Ivaylo; Stankovic, Ranka; Perdih, Andrej; Gabrovsek, Dejan (National University of Ireland Galway, 2020-05-16)
    Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually ...

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