@inproceedings{mccrae-arcan-2020-nuig,
    title = "{NUIG} at {TIAD}: Combining Unsupervised {NLP} and Graph Metrics for Translation Inference",
    author = "McCrae, John Philip  and
      Arcan, Mihael",
    editor = "Kernerman, Ilan  and
      Krek, Simon  and
      McCrae, John P.  and
      Gracia, Jorge  and
      Ahmadi, Sina  and
      Kabashi, Besim",
    booktitle = "Proceedings of the 2020 Globalex Workshop on Linked Lexicography",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.globalex-1.15/",
    pages = "92--97",
    language = "eng",
    ISBN = "979-10-95546-46-7",
    abstract = "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 multi-way neural machine translation method. The results are an improvement over our previous system and produce the highest precision among all systems in the task as well as very competitive F-Measure results. Incorporating features from other systems should be easy in the framework we describe in this paper, suggesting this could very easily be extended to an even stronger result."
}