1. A method of optimizing search engine performance comprising: receiving from a user a seed string including one or more letters; generating at least one search query based on the seed string; executing a search associated with each of the at least one search query, the search query including at least one of an example, suggestion, or a term; generating a set of search results based on the executed search; retrieving, from a data source different than a data source used by the search, a previously stored set of expected results associated with the search query, wherein the previously stored set of expected results is distinct from the set of search results generated in response to receiving the seed string, and wherein the expected results have a predetermined degree of relevance to the search query; determining a search query evaluation value for each of the at least one search query based at least in part on comparing the set of search results associated with each of the at least one search query with the previously stored set of expected results, wherein the search query evaluation value includes one or more of a precision value or a recall value; determining a mean relevancy value for each of the at least one search query, wherein the mean relevancy value is based on a plurality of relevancy values calculated based on different weighting of the search query evaluation value associated with the at least one search query; and configuring a search criteria of the search engine based on the mean relevancy value, the configured search criteria for use in a subsequent search after the set of search results have been generated.
1. A method of optimizing search engine performance comprising: receiving from a user a seed string including one or more letters; generating at least one search query based on the seed string; executing a search associated with each of the at least one search query, the search query including at least one of an example, suggestion, or a term; generating a set of search results based on the executed search; retrieving, from a data source different than a data source used by the search, a previously stored set of expected results associated with the search query, wherein the previously stored set of expected results is distinct from the set of search results generated in response to receiving the seed string, and wherein the expected results have a predetermined degree of relevance to the search query; determining a search query evaluation value for each of the at least one search query based at least in part on comparing the set of search results associated with each of the at least one search query with the previously stored set of expected results, wherein the search query evaluation value includes one or more of a precision value or a recall value; determining a mean relevancy value for each of the at least one search query, wherein the mean relevancy value is based on a plurality of relevancy values calculated based on different weighting of the search query evaluation value associated with the at least one search query; and configuring a search criteria of the search engine based on the mean relevancy value, the configured search criteria for use in a subsequent search after the set of search results have been generated. 9. The method of claim 1 , wherein configuring the search criteria includes updating a dictionary of terms associated with the search engine.