The Monthly Labor Review (MLR) is published by the U.S. Bureau of Labor Statistics. Issues of the MLR often focus on a particular topic, and most articles are written by BLS staff. The need for a classification system of past MLR articles that can be used to label future articles has been recognized by the agency. To address this problem, we employed various unsupervised learning approaches to cluster MLR articles from 2000 to 2013. In this presentation, we will discuss the processes used to prepare the data set, the cluster approaches used, and the results.