@InProceedings{trost-klakow:2017:TextGraphs-11,
  author    = {Trost, Thomas Alexander  and  Klakow, Dietrich},
  title     = {Parameter Free Hierarchical Graph-Based Clustering for Analyzing Continuous Word Embeddings},
  booktitle = {Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {30--38},
  abstract  = {Word embeddings are high-dimensional vector representations of words and are
	thus difficult to interpret. In order to deal with this, we introduce an
	unsupervised parameter free method for creating a hierarchical graphical
	clustering of the full ensemble of word vectors and show that this structure is
	a geometrically meaningful representation of the original relations between the
	words. This newly obtained representation can be used for better understanding
	and thus improving the embedding algorithm and exhibits semantic meaning,
	so it can also be utilized in a variety of language processing tasks like
	categorization or measuring similarity.},
  url       = {http://www.aclweb.org/anthology/W17-2404}
}