Patent Document ID: 9009045
Application ID: 14183346

Base Claim:
1. A method comprising: selecting, by a model-driven candidate-sorting tool executing on a processing device, a data set of digital interview data for model-driven candidate sorting, wherein the data set comprises candidate data recorded for a plurality of interviewing candidates; for the plurality of interviewing candidates, analyzing, by the model-driven candidate-sorting tool, the candidate data for the respective interviewing candidate to identify a plurality of digital interviewing cues; and applying the digital interviewing cues to a prediction model to predict an achievement index based on the plurality of digital interviewing cues identified for the respective interviewing candidate, wherein the applying the plurality of digital interviewing cues to the prediction model to predict the achievement index is performed without reviewer input at the model-driven candidate-sorting tool; sorting a list of the plurality of interviewing candidates based on the predicted achievement indices from the applying the plurality of digital interviewing cues to the prediction model; and presenting the sorted list of the plurality of interviewing candidates in a user interface to a reviewer.

---

Claim 14:
14. The method of claim 1 , further comprising: obtaining a historical data set of interview cues; storing the historical data set of interview cues in a cue matrix, wherein rows of the cue matrix each represent one of a plurality of past candidates and columns of the cue matrix represent each of the interview cues; storing past achievement indices of the plurality of candidates in an achievement score vector; building the prediction model using the cue matrix and the achievement score vector, wherein the cue matrix represents an input matrix of a system identification algorithm and the achievement score vector represents an output matrix of the system identification algorithm; and training the prediction model.