1. A computer implemented system that facilitates obtaining search query results, comprising a computer readable medium having stored thereon: a plurality of search query result ranking components, including a learning component, that receive search query results and separately determine search query rankings for the search query utilizing, at least in part, a property store, the learning component differentiates between implicit and explicit user search query feedback in determining search query rankings; and a relevance component that determines an optimum search query result relevancy ranking via aggregation of the separately determined search query rankings at least in part by: determining a first set of highest ranking n results from the search query results in terms of OKAPI ranking, where n is an integer from one to infinity; selecting scores that are coerced via a best bets procedure and moving them to a top of the first set; determining a second set of highest ranking n results from the search query results in terms of a learning relevance score; merging the first and second sets of highest ranking n results via one-to-P interleaving, where P is an integer from one to infinity; removing duplicate results; and returning a first n results of the merged set.
1. A computer implemented system that facilitates obtaining search query results, comprising a computer readable medium having stored thereon: a plurality of search query result ranking components, including a learning component, that receive search query results and separately determine search query rankings for the search query utilizing, at least in part, a property store, the learning component differentiates between implicit and explicit user search query feedback in determining search query rankings; and a relevance component that determines an optimum search query result relevancy ranking via aggregation of the separately determined search query rankings at least in part by: determining a first set of highest ranking n results from the search query results in terms of OKAPI ranking, where n is an integer from one to infinity; selecting scores that are coerced via a best bets procedure and moving them to a top of the first set; determining a second set of highest ranking n results from the search query results in terms of a learning relevance score; merging the first and second sets of highest ranking n results via one-to-P interleaving, where P is an integer from one to infinity; removing duplicate results; and returning a first n results of the merged set. 2. The system of claim 1 , the relevance component employs a weighted summation to facilitate in the aggregation of the separately determined search query rankings.