Patent ID: 11971899
Assignee: ICIMS, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 12:
13. The apparatus of claim 8, wherein the plurality of search engines is a first plurality of search engines, the plurality of ballots is a first plurality of ballots, the mathematical representation is a first mathematical representation, the normalized mathematical representation is a first normalized mathematical representation, the vector is a first vector, and the output is a first output, and the processor is further configured to:
train a statistical model to generate the trained statistical model;
receive a second plurality of ballots from a second plurality of search engines having a Z number of search engines,
search engines in the Z search engines being different than search engines in the X search engines, Z being at least two, the second plurality of ballots associated with N number of candidates, N being at least two, each ballot from the second plurality of ballots (1) generated based on a search engine from the second plurality of search engines different than remaining search engines from the second plurality of search engines and (2) indicating how the search engine ranked the N candidates;

generate a second mathematical representation based on the second plurality of ballots, the mathematical representation having a size N by N,
for each candidate from the N candidates and for each remaining candidate from the N candidates, the second mathematical representation indicating a number of search engines from the second plurality of search engines that ranked that candidate higher than that remaining candidate;

generate a second normalized mathematical representation by dividing each value in the second mathematical representation by Z;
generate a second vector based on the second normalized mathematical representation; and
input the second vector to the trained statistical model to generate a second output, the trained statistical model not further trained after the training the statistical model to generate the trained statistical model and before the inputting the second vector to the trained statistical model, the second output indicating a ranking of the N candidates.