@inproceedings{shi-etal-2016-real,
    title = "Real Multi-Sense or Pseudo Multi-Sense: An Approach to Improve Word Representation",
    author = "Shi, Haoyue  and
      Li, Caihua  and
      Hu, Junfeng",
    editor = "Brunato, Dominique  and
      Dell{'}Orletta, Felice  and
      Venturi, Giulia  and
      Fran{\c{c}}ois, Thomas  and
      Blache, Philippe",
    booktitle = "Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity ({CL}4{LC})",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W16-4109/",
    pages = "79--88",
    abstract = "Previous researches have shown that learning multiple representations for polysemous words can improve the performance of word embeddings on many tasks. However, this leads to another problem. Several vectors of a word may actually point to the same meaning, namely pseudo multi-sense. In this paper, we introduce the concept of pseudo multi-sense, and then propose an algorithm to detect such cases. With the consideration of the detected pseudo multi-sense cases, we try to refine the existing word embeddings to eliminate the influence of pseudo multi-sense. Moreover, we apply our algorithm on previous released multi-sense word embeddings and tested it on artificial word similarity tasks and the analogy task. The result of the experiments shows that diminishing pseudo multi-sense can improve the quality of word representations. Thus, our method is actually an efficient way to reduce linguistic complexity."
}