UMND2: SenseClusters applied to the sense induction task of SENSEVAL-4

SenseClusters is a freely-available open- source system that served as the University of Minnesota, Duluth entry in the SENSEVAL-4 sense induction task. For this task SenseClusters was configured to construct representations of the instances to be clustered using the centroid of word cooccurrence vectors that replace the words in an instance. These instances are then clustered using k-means where the number of clusters is discovered automatically using the Adapted Gap Statistic. In these experiments SenseClusters did not use any information outside of the raw untagged text that was to be clustered, and no tuning of the system was performed using external corpora.