1. A computer implemented method for clustering content according to similarity, the method comprising: receiving a set of features for a plurality of content items; calculating, by a processor, a distance matrix for the plurality of content items based on user navigation of at least some of the content items; labeling, by a processor, at least some of the content items as pairwise constraints based on the distance matrix; creating, by a processor, a boosted cluster by incorporating the pairwise constraints into a clustering algorithm; applying a pattern analysis to the boosted cluster; and modifying the boosted cluster based on relations identified by the pattern analysis.
1. A computer implemented method for clustering content according to similarity, the method comprising: receiving a set of features for a plurality of content items; calculating, by a processor, a distance matrix for the plurality of content items based on user navigation of at least some of the content items; labeling, by a processor, at least some of the content items as pairwise constraints based on the distance matrix; creating, by a processor, a boosted cluster by incorporating the pairwise constraints into a clustering algorithm; applying a pattern analysis to the boosted cluster; and modifying the boosted cluster based on relations identified by the pattern analysis. 7. The method of claim 1 , further comprising identifying topical tags from at least one of an activity log of a search query, markup language code, and text mining.