Optimization of server selection using euclidean analysis of search terms

Abstract

Euclidean analysis is used to define queries in terms of a multi-axis query space where each of the keywords T1, T2, . . . Ti, . . . Tn is assigned an axis in that space. Sets of test queries St each one from one of a plurality of server sources are plotted in the query space. Clusters of the search terms are identified based on the proximity of the plotted query vectors to one another. Predominant servers are identified for each of the clusters. When a search query Ss is received, the location of its vector is determined and the servers accessed by the search query Ss are those that are predominant in the cluster which its vector may fall or is in closest proximity to.

Dependencies are inferred from the claim text.