1. A computer-implemented method, comprising: selecting a plurality of search queries; grouping the plurality of search queries into one or more clusters, wherein grouping further comprises: assigning each of the plurality of search queries to a cluster in a total number of clusters; designating one of the search queries assigned to each cluster as a cluster center for the each cluster; and adjusting one or more of (i) the total number of clusters, (ii) an assignment of search queries to the clusters, and (iii) a designation of cluster centers for the clusters, to minimize an aggregated metric of all search queries, where a metric of a search query is between the search query and the cluster center of the cluster comprising the search query; selecting a representative query for each cluster; associating each cluster with a respective representative category; assigning a respective rank to each of the clusters, the assigning being based on a cluster popularity score of each cluster and a category popularity score of each cluster's respective representative category; and presenting the selected representative queries in order according to the ranks of their respective clusters, wherein assigning a respective rank to each of the clusters is performed on one or more processors.
1. A computer-implemented method, comprising: selecting a plurality of search queries; grouping the plurality of search queries into one or more clusters, wherein grouping further comprises: assigning each of the plurality of search queries to a cluster in a total number of clusters; designating one of the search queries assigned to each cluster as a cluster center for the each cluster; and adjusting one or more of (i) the total number of clusters, (ii) an assignment of search queries to the clusters, and (iii) a designation of cluster centers for the clusters, to minimize an aggregated metric of all search queries, where a metric of a search query is between the search query and the cluster center of the cluster comprising the search query; selecting a representative query for each cluster; associating each cluster with a respective representative category; assigning a respective rank to each of the clusters, the assigning being based on a cluster popularity score of each cluster and a category popularity score of each cluster's respective representative category; and presenting the selected representative queries in order according to the ranks of their respective clusters, wherein assigning a respective rank to each of the clusters is performed on one or more processors. 2. The method of claim 1 wherein selecting the representative query for each query cluster further comprises: selecting the representative query based on a query popularity score for each search query in the cluster, where the query popularity score for a search query is based on a rate of increase in search volume for the search query or a total search volume for the search query.