1. A computer-implemented method comprising: identifying one or more first subject matter categories in a plurality of subject matter categories, each of the first subject matter categories being a hierarchical classification of a plurality of confirmed valid search results for queries, and wherein at least one query for each identified first subject matter category includes a term in text; for each first subject matter category in the first subject matter categories: selecting one or more terms wherein each of the one or more terms occurs in the text and in one or more queries having confirmed valid search results that are in the first subject matter category; identifying one or more terms from the selected terms that each match a refinement level in the first subject matter category hierarchical classification; boosting an initial weight of the first subject matter category by a value based on the refinement level to acquire a first boosted weight; boosting the first boosted weight by a value based on a count of the selected terms to acquire a second boosted weight; selecting the first matter category if the second boosted weight satisfies a first threshold; and recommending content associated with one or more of the selected first subject matter categories.