@InProceedings{qasemizadeh2016Computerm2016,
  author      = {Qasemizadeh, Behrang},
  title       = {A Study on the Interplay Between the Corpus Size and Parameters of a Distributional Model for Term Classification},
  booktitle   = {Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016)},
  year        = {2016},
  number      = {Patrick Drouin and Natalia Grabar and Thierry Hamon and Kyo Kageura and Koichi Takeuchi},
  pages       = {62--72},
  address     = {Osaka, Japan},
  month       = {December},
  publisher   = {The COLING 2016 Organizing Committee},
  abstract    = {We propose and evaluate a method for identifying co-hyponym lexical units in a
 terminological resource. The principles of term recognition and distributional
 semantics are combined to extract terms from a similar category of concept.
 Given a set of candidate terms, random projections are employed to represent
 them as low-dimensional vectors. These vectors are derived automatically from
 the frequency of the co-occurrences of the candidate terms and words that
 appear within windows of text in their proximity (context-windows). In a
 $k$-nearest neighbours framework, these vectors are classified using a small
 set of manually annotated terms which exemplify concept categories. We then
 investigate the interplay between the size of the corpus that is used for
 collecting the co-occurrences and a number of factors that play roles in the
 performance of the proposed method: the configuration of context-windows for
 collecting co-occurrences, the selection of neighbourhood size ($k$), and the
 choice of similarity metric.},
  pdffilename = {computerm_2016_term_classification},
  url         = {http://aclweb.org/anthology/W16-4708},
}