In this paper we have presented a set of algorithms for finding the real referents for ambiguous personal names in text using unsupervised clustering and feature extraction methods.
we have shown how to learn and use automatically extracted biographic information to improve clustering results, and have demonstrated this improvement by evaluating on pseudonames.