Abstract: A system for serving advertisements determines the frequency of occurrence for each parameter of a plurality of parameters associated with a plurality of search queries. The plurality of parameters are associated with one or more advertisements. The system stores at least some parameters to a first storage based on the frequency of occurrence of the parameters. The system stores the other parameters to a second storage that has a higher latency than the first storage. When serving advertisements, the system ranks advertisements for delivery based on the parameters stored in the first storage device and the second storage.

Abstract: A system for serving advertisements determines the frequency of occurrence for each parameter of a plurality of parameters associated with a plurality of search queries. The plurality of parameters are associated with one or more advertisements. The system stores at least some parameters to a first storage based on the frequency of occurrence of the parameters. The system stores the other parameters to a second storage that has a higher latency than the first storage. When serving advertisements, the system ranks advertisements for delivery based on the parameters stored in the first storage device and the second storage.

Abstract: An advanced system and method for optimizing selection of online advertisements is provided. Decision trees with expressions to evaluate feature values for advertisements may be received, and a decision tree similarity matrix of decision tree similarity values between pairs of decision trees may be generated that represent the number of common features between two decision trees. The edges of the decision tree similarity matrix may be sorted in non-increasing order by edge value, and the decision trees of each edge retrieved from the sorted order may be placed in an optimized sequence order for evaluation. In response to a request to serve advertisements, advertisements may be scored by evaluating the decision trees of advertisements in the optimized sequence order. The advertisements may then be ranked in descending order by score, and advertisement with the highest scores may be sent for display.

Abstract: A method and a system are provided for enabling high performance ad selection. In one example, the system receives an ad. A relevance of the ad needs to be determined. The relevance is a function of one or more computational intensive functions. A computational intensive function is a function that requires more than trivial processing. The system identifies one or more arguments of the computational intensive functions that are within a fixed range. The system generates a tableau based on the one or more arguments that are within a fixed range. The tableau is configured to benefit run-time performance of an ad selection process whenever the computer uses the pre-generated tableau during run-time instead of calculating one or more computational intensive functions.

Abstract: Methods and systems are provided for determining whether to use a full sort sorting technique or a merge sort sorting technique to sort a partially sorted list or data set. One or more tables may be utilized to allow such a determination to be made with regard to a first partially sorted list based on parameters associated with the list including a data distribution type, a number of data items in the list, and a ratio of sorted items to unsorted items in the list.