7. A product for discovering the intent of a query comprising: a memory; and instructions stored on the memory that, when executed, cause a computer processor to: analyze log data stored on the memory relating to a user query submitted by a user to one or more search engines; identify a plurality of related queries that are suggested to the user, where the identified related queries are related to the first query; analyze log data stored on the memory relating to the related queries; construct a first frequency vector for the user query and a related frequency vector for each of the related queries based on the analyzing, wherein the first frequency vector comprises an array of first query frequency score entries, each first query frequency score entry corresponding a different search engine in a set of search engines, wherein each related frequency vector comprises an array of related query frequency score entries, each related query frequency score entry corresponding to a different search engine in the set of search engines, and wherein each array has a length equal to the number of search engines in a set of search engines; determine a query intent vector comprising an array of entries, wherein the array has a length equal to the number of search engines in the seat of search engines, wherein each entry corresponds to a different search engine of the set of search engines, and wherein the intent of the user query is derived from the query intent vector; compare each entry of the query intent vector to a threshold; for each entry of the query intent vector that exceeds the threshold, identify the search engine of the set of search engines that corresponds to that entry; and provide search results to the user based on a search of the first query on the identified search engines.
7. A product for discovering the intent of a query comprising: a memory; and instructions stored on the memory that, when executed, cause a computer processor to: analyze log data stored on the memory relating to a user query submitted by a user to one or more search engines; identify a plurality of related queries that are suggested to the user, where the identified related queries are related to the first query; analyze log data stored on the memory relating to the related queries; construct a first frequency vector for the user query and a related frequency vector for each of the related queries based on the analyzing, wherein the first frequency vector comprises an array of first query frequency score entries, each first query frequency score entry corresponding a different search engine in a set of search engines, wherein each related frequency vector comprises an array of related query frequency score entries, each related query frequency score entry corresponding to a different search engine in the set of search engines, and wherein each array has a length equal to the number of search engines in a set of search engines; determine a query intent vector comprising an array of entries, wherein the array has a length equal to the number of search engines in the seat of search engines, wherein each entry corresponds to a different search engine of the set of search engines, and wherein the intent of the user query is derived from the query intent vector; compare each entry of the query intent vector to a threshold; for each entry of the query intent vector that exceeds the threshold, identify the search engine of the set of search engines that corresponds to that entry; and provide search results to the user based on a search of the first query on the identified search engines. 11. The product of claim 7 , wherein the related queries are identified based on a concept network associated with the user query.