Queries submitted to the Excite search engine were analyzed for subject content based on the cooccurrence of terms within multiterm queries. More than 1000 of the most frequently cooccurring term pairs were categorized into one or more of 30 developed subject areas. Subject area frequencies and their cooccurrences with one another were tallied and analyzed using hierarchical cluster analysis and multidimensional scaling. The cluster analyses revealed several anticipated and a few unanticipated groupings of subjects, resulting in several well-defined high-level clusters of broad subject areas. Multidimensional scaling of subject cooccurrences revealed similar relationships among the different subject categories. Applications that arise from a better understanding of the topics users search and their relationships are discussed.