@InProceedings{shi-li-hu:2016:CL4LC,
  author    = {Shi, Haoyue  and  Li, Caihua  and  Hu, Junfeng},
  title     = {Real Multi-Sense or Pseudo Multi-Sense: An Approach to Improve Word Representation},
  booktitle = {Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  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.},
  url       = {http://aclweb.org/anthology/W16-4109}
}