Patent Document ID: 7849076
Application ID: 12060195

Base Claim:
1. A method for learning ranking functions to determine the ranking of one or more content items that are responsive to a query, the method comprising: generating one or more training sets comprising one or more content item-query pairs; determining one or more contradicting pairs in a given training set; formulating an optimization function to minimize the number of contradicting pairs in the training set using a functional iterative method that comprises applying an isotonic regression function within each query and using the output to determine regression targets for each content item-query pair in a next iteration; modifying the optimization function by incorporating a grade difference between one or more content items corresponding to the query in the training set; applying the optimization function to each query in the training set; determining a ranking function based on an application of regression trees on the one or more queries of the training set minimized by the optimization function; and storing the ranking function for application to content item-query pairs not contained in the one or more training sets.

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Claim 6:
6. The method of claim 1 , wherein generating one or more training sets comprising one or more content item-query pairs further comprises determining a relevance label based on historical click through data for a given content item-query pair.