1. A computer-implemented method of selecting a content item from a content item database, the method comprising: accessing an incoming query from a memory device; creating a first set of tokens from the incoming query; computing a first total as a number of tokens in the first set of tokens; accessing a second set of tokens corresponding to the content item stored in the content item database; determining, with at least one processor, a degree of similarity by: determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens; computing a randomized easy signature by: selecting a set of most frequent tokens from the second set of tokens; computing a second total as a number of tokens in the selected set of most frequent tokens; randomly selecting a sub-set of tokens from the selected set of most frequent tokens; determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and selecting, with the at least one processor, the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold.
1. A computer-implemented method of selecting a content item from a content item database, the method comprising: accessing an incoming query from a memory device; creating a first set of tokens from the incoming query; computing a first total as a number of tokens in the first set of tokens; accessing a second set of tokens corresponding to the content item stored in the content item database; determining, with at least one processor, a degree of similarity by: determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens; computing a randomized easy signature by: selecting a set of most frequent tokens from the second set of tokens; computing a second total as a number of tokens in the selected set of most frequent tokens; randomly selecting a sub-set of tokens from the selected set of most frequent tokens; determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and selecting, with the at least one processor, the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold. 4. The computer-implemented method of claim 1 , wherein determining the degree of similarity further comprises computing an average randomized easy signature by performing the steps of: computing a plurality of randomized easy signatures; and averaging the plurality of randomized easy signatures.