Clustering for Name Disambiguation in Author Citations

In this paper, we propose a clustering method for disambiguating abbreviated author names appearing in citation data by finding the correct full name for each instance of an abbreviated name. We use the standard naive Bayes mixture model and the two-variable mixture model, which is a newly proposed model having two hidden variables. In the experiment, we have used the DBLP data set and have selected 47 abbreviated author names corresponding to more than or equal to 50 full names for evaluation. The results show that our mode