Knowing the number of different individuals carrying the same name may improve the overall accuracy of a Person Cross Document Coreference System, which processes large corpora and clusters the name mentions according to the individuals carrying them. In this paper we present a series of methods of estimating this number. In particular, an estimation method based on name perplexity, which brings a large improvement over the baseline given by the gap statistics, is instrumental in reaching accurate clustering results because not only it can predict the number of clusters with a very good confidence, but also it can indicate what type of clustering method works best for each particular name.
Methods of estimating the number of clusters for person cross document coreference task
Popescu, Octavian;Zanoli, Roberto
2012-01-01
Abstract
Knowing the number of different individuals carrying the same name may improve the overall accuracy of a Person Cross Document Coreference System, which processes large corpora and clusters the name mentions according to the individuals carrying them. In this paper we present a series of methods of estimating this number. In particular, an estimation method based on name perplexity, which brings a large improvement over the baseline given by the gap statistics, is instrumental in reaching accurate clustering results because not only it can predict the number of clusters with a very good confidence, but also it can indicate what type of clustering method works best for each particular name.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
