From neighborhood to parenthood: the advantages of dependency representation over bigrams in Brown clustering
Simon Šuster, Gertjan van Noord · University of Groningen research database (University of Groningen / Centre for Information Technology) · 2014
We present an effective modification of the popular Brown et al. 1992 word clustering algorithm, using a dependency language model. By leveraging syntax-based context, resulting clusters are better when evaluated against a wordnet for Dutch. The improvements are stable across parameters such as number of clusters, minimum frequency and granularity. Further refinement is possible through dependency relation selection. Our approach achieves a desired clustering quality with less data, resulting in a decrease in cluster creation times.