Integrated explicit intent and inference based job seeker identification and segmentation

Abstract

In an example embodiment, a specialized machine learned model, called a look-alike model, is trained using a machine learning algorithm to predict future job engagement for a user. This look-alike model is then used to create new segments on top of the segments provided by a rules-based approach. Specifically, the look-alike model is designed to take users who have been segmented by a rule-based approach into an 'inactive job seeker' categorization (such as those assigned to the resting users and dormant users segments) and calculate a predicted job engagement score for these users. Based on the predicted job engagement score, a user may then be reassigned from one of the inactive job seeker categorizations to one of one or more new job seeker categorizations (such as predicted open job seekers or predicted opportunistic job seekers).