Distilling Relevant Documents by Means of Dynamic Quantum Clustering

Dynamic Quantum Clustering (DQC) is a recent clustering technique based on physical intuition from quantum mechanics. Clusters are identified as the minima of the potential function of the Schr\uf6dinger equation. In this poster, we apply this technique to explore the possibility to select highly relevant documents relative to a query of a user. In particular, we analyze the clusters produced by DQC with a standard test collection