@inproceedings{Stevenson2,
  author = "Suzanne Stevenson and Eric Joanis",
  title = "Semi-supervised Verb Class Discovery Using Noisy Features",
  booktitle = "In Proceedings of the Seventh Conference on Natural Language Learning (CoNLL-2003)",
  address = "Edmonton, Canada",
  month = "June",
  year = "2003",
  abstract = "<p>We cluster verbs into lexical semantic classes, using a general set of
             noisy features that capture syntactic and semantic properties of the
             verbs.  The feature set was previously shown to work well in a
             supervised learning setting, using known English verb classes.  In
             moving to a scenario of verb class discovery, using clustering, we
             face the problem of having a large number of irrelevant features for a
             particular clustering task.  We investigate various approaches to
             feature selection, using both unsupervised and semi-supervised
             methods, comparing the results to subsets of features manually chosen
             according to linguistic properties.  We find that the unsupervised
             method we tried cannot be consistently applied to our data.  However,
             the semi-supervised approach (using a seed set of sample verbs)
             overall outperforms not only the full set of features, but the
             hand-selected features as well.</p>",
  download = "http://www.cs.toronto.edu/~joanis/Papers/CoNLL03-StevensonJoanis.pdf"
}