Microsoft Corporation
Search optimization based on relevant-parameter selection

Abstract:

Methods, systems, and computer programs are presented for search optimization based on relevant-parameter selection. One method includes an operation for training a machine-learning program with information about users of an online service to generate a machine-learning model that calculates parameter preference scores for a plurality of parameters. Further, the method includes operations for detecting a job search for a user, identifying user parameters associated with the user, and calculating, by the machine-learning model, the parameter preference scores for the user parameters. Further, search parameters are determined by selecting a predetermined number of user parameters base on the parameter preference scores. A search of a job-postings database is performed with the search parameters, and the results are presented on a display.