@inproceedings{Brooke4,
   author = {Julian Brooke and Tong Wang and Graeme Hirst},
   title = {Predicting word clipping with latent semantic analysis},
   address = {Chiang Mai, Thailand},
   booktitle = {Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP-2011)},
   pages = {???--???},
   year = {2011},
   download = {http://ftp.cs.toronto.edu/pub/gh/Brooke-etal-IJCNLP-2011.pdf},
   abstract = {We compare a resource-driven appraach
                  with a task-specific classification model for a
                  new near-synonym word choice sub-task, predicting
                  whether a full or a clipped form of a word will be
                  used (e.g. doctor or doc) in a given context. Our
                  results indicate that the resource-driven approach,
                  the use of a formality lexicon, can provide
                  competitive perfo mance, with the parameters of
                  the task-specific model mirroring the parameters
                  under which the lexicon was built.}
}