@inproceedings{gogoi-etal-2020-assamese,
    title = "{A}ssamese Word Sense Disambiguation using Genetic Algorithm",
    author = "Gogoi, Arjun  and
      Baruah, Nomi  and
      Sarma, Shikhar Kr.",
    editor = "Bhattacharyya, Pushpak  and
      Sharma, Dipti Misra  and
      Sangal, Rajeev",
    booktitle = "Proceedings of the 17th International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2020",
    address = "Indian Institute of Technology Patna, Patna, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.icon-main.40/",
    pages = "303--307",
    abstract = "Word sense disambiguation (WSD) is a problem to determine a word according to a context in which it occurs. There are plenty amount of works done in WSD for some languages such as English, but research work on Assamese WSD remains limited. It is a more exigent task because Assamese has an intrinsic complexity in its writing structure and ambiguity, such as syntactic, semantic, and anaphoric ambiguity levels.A novel unsupervised genetic word sense disambiguation algorithm is proposed in this paper. The algorithm first uses WordNet to extract all possible senses for a given ambiguous word, then a genetic algorithm is used taking Wu-Palmer{'}s similarity measure as the fitness function and calculating the similarity measure for all extracted senses. The winner sense which will have the highest score declared as he winner sense."
}