Recent Submissions

  • 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 ...
  • Defying Wikidata: Validation of terminological relations in the web of data 

    Martín-Chozas, Patricia; Ahmadi, Sina; Montiel-Ponsoda, Elena (National University of Ireland Galway, 2020-05-16)
    In this paper we present an approach to validate terminological data retrieved from open encyclopaedic knowledge bases. This need arises from the enrichment of automatically extracted terms with information from existing ...
  • Taxonomy extraction for customer service knowledge base construction 

    Pereira, Bianca; Robin, Cécile; Daudert, Tobias; McCrae, John P.; Mohanty, Pranab; Buitelaar, Paul (Springer, 2019-11-04)
    Customer service agents play an important role in bridging the gap between customers vocabulary and business terms. In a scenario where organisations are moving into semi-automatic customer service, se- mantic technologies ...
  • Detecting bot behaviour in social media using digital DNA compression 

    Pasricha, Nivranshu; Hayes, Conor (AICS (Artificial Intelligence and Cognitive Science) 2019, 2019-12-05)
    A major challenge faced by online social networks such as Facebook and Twitter is the remarkable rise of fake and automated bot accounts over the last few years. Some of these accounts have been reported to engage in ...
  • 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 ...
  • Truth or lie: Automatically fact checking news 

    Azevedo, Lucas (ACM, 2018-04-23)
    In the actual scenario of ever-growing data consumption speed and quantity, factors like news source decentralization, citizen journalism and democratization of media, make the task of manually checking and correcting ...
  • Creating a multilingual terminological resource using linked data:the case of archaeological domain in the Italian language 

    Carlino, Carola; Ahmadi, Sina; Speranza, Giulia (CEUR Workshop Proceedings, 2019-11-13)
    The lack of multilingual terminological resources in specialized domains constitutes an obstacle to the access and reuse of information. In the technical domain of cultural heritage and, in particular, archaeology, such ...
  • Towards electronic lexicography for the Kurdish language 

    Ahmadi, Sina; Hassani, Hossein; McCrae, John P. (eLex 2019, 2019-10-01)
    This paper describes the development of lexicographic resources for Kurdish and provides a lexical model for this language. Kurdish is considered a less-resourced language, and currently, lacks machine-readable lexical ...
  • 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 ...
  • 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 ...
  • 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 ...
  • TIAD 2019 Shared Task: Leveraging knowledge graphs with neural machine translation for automatic multilingual dictionary generation 

    Torregrosa, Daniel; Arcan, Mihael; Ahmadi, Sina; McCrae, John P. (National University of Ireland, Galway, 2019-04-20)
    This paper describes the different proposed approaches to the TIAD 2019 Shared Task, which consisted in the automatic discovery and generation of dictionaries leveraging multilingual knowledge bases. We present three methods ...
  • An evaluation of SPARQL federation engines over multiple endpoints 

    Saleem, Muhammad; Khan, Yasar; Hasnain, Ali; Ermilov, Ivan; Ngonga Ngomo, Axel-Cyrille (NUI Galway, 2018-04-23)
    Due to decentralized and linked architecture underlying Linking Data, running complex queries often require collecting data from multiple RDF datasets. The optimization of the runtime of such queries, called federated ...
  • Drug target discovery using knowledge graph embeddings 

    Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Association for Computing Machinery, 2019-04-08)
    The field of drug discovery has entered a plateau stage lately. It is increasingly more expensive and time-demanding to introduce new drugs into the market. One of the main reasons is the slow progress in finding novel ...
  • Link prediction using multi part embeddings 

    Mohamed, Sameh K.; Nováček, Vít (NUI Galway, 2019-06-02)
    Knowledge graph embeddings models are widely used to provide scalable and efficient link prediction for knowledge graphs. They use different techniques to model embeddings interactions, where their tensor factorisation ...
  • Knowledge base completion using distinct subgraph paths 

    Mohamed, Sameh K.; Nováček, Vít; Vandenbussche, Pierre-Yves (ACM, 2018-04-09)
    Graph feature models facilitate efficient and interpretable predictions of missing links in knowledge bases with network structure (i.e. knowledge graphs). However, existing graph feature models-e.g. Subgraph Feature ...

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