Browsing Data Science Institute (Workshop Papers) by Author "http://dx.doi.org/10.13039/501100007601"

Now showing items 1-9 of 9

    • Challenges of word sense alignment: Portuguese language resources 

      Salgado, Ana; Ahmadi, Sina; Simões, Alberto; McCrae, John P.; Costa, Rute (National University of Ireland Galway, 2020-05-16)
      This paper reports on an ongoing task of monolingual word sense alignment in which a comparative study between the Portuguese Academy of Sciences Dictionary and the Dicionario Aberto ´ is carried out in the context of the ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Multimodal meme dataset (MultiOFF) for identifying offensive content in image and text 

      Suryawanshi, Shardul; Chakravarthi, Bharathi Raja; Arcan, Mihael; Buitelaar, Paul (European Language Resources Association (ELRA), 2020-05-11)
      A meme is a form of media that spreads an idea or emotion across the internet. As posting meme has become a new form of communication of the web, due to the multimodal nature of memes, postings of hateful memes or related ...

    • NUIG at TIAD: Combining unsupervised NLP and graph metrics for translation inference 

      McCrae, John P.; Arcan, Mihael (European Language Resources Association (ELRA), 2020-05-11)
      In this paper, we present the NUIG system at the TIAD shard task. This system includes graph-based metrics calculated using novel algorithms, with an unsupervised document embedding tool called ONETA and an unsupervised ...

    • On lexicographical networks 

      Ahmadi, Sina; Arcan, Mihael; McCrae, John (NUI Galway, 2018-12-06)
      In this study, we analyze various aspects of lexicographical networks. We would like to answer our research questions of what are the characteristics of the lexicographical networks? In addition to the existing notions of ...

    • 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 ...