Predicting Word Clipping with Latent Semantic Analysis
Julian Brooke, Tong Wang, Graeme Hirst · 2011
In this paper, we compare a resource-driven approach with a task-specific clas-sification 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 con-text. Our results indicate that the resource-driven approach, the use of a formality lexicon, can provide competitive perfor-mance, with the parameters of the task-specific model mirroring the parameters under which the lexicon was built. 1