Learning a Distance Metric to cluster E-Mails

Application of document clustering techniques to cluster e-mails is an interesting application. Techniques like kmeans, EM etc can be used to achieve this. However, the selection of a good distance metric is the key issue involved. Often people manually tweak the chosen distance metric to achieve desirable/good clusters/results that in all certainty do not provide a generic solution. Hence it would be very useful to automatically learn the distance metric from some training set before clustering. In [1] a technique for learning distance metrics has been proposed for clustering. Our first task is to apply this technique to document (specifically e-mails) clustering.