1. A computer-implemented method comprising: receiving resource that includes a set of words; identifying a set of candidate clusters from a probabilistic model that are classified as likely to be active in generating the set of words; generating a vector that characterizes the resource, wherein, for each cluster of the set of candidate clusters, a component of the vector indicates a degree to which the cluster was active in generating the set of words; and using the vector in performing an operation related to the resource.
2. The method of claim 1 , wherein identifying a set of candidate clusters from a probabilistic model that are classified as likely to be active in generating the set of words comprises: generating an evidence tree for the set of words, wherein the evidence tree identifies one or more clusters that each link to terminal nodes associated with the set of words; determining, using the evidence tree and for each cluster, a respective likelihood that the cluster is active in generating the set of words; and selecting one or more of the clusters as candidate clusters based on their respective likelihoods.