The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jan. 28, 2025
Filed:
Jun. 07, 2023
Zeta Global Corp., New York, NY (US);
Barney Govan, Walnut Creek, CA (US);
Wynn Vonnegut, San Francisco, CA (US);
Christian Monberg, San Francisco, CA (US);
Zeta Global Corp., New York, NY (US);
Abstract
A computer-implemented method for generating content recommendations for content items, each content item associated with one of a plurality of customers, the method comprising: receiving, by a network-connected server, a content request from a requesting user, the content request comprising a user identifier and a customer identifier; retrieving request parameters from a computer-implemented parameter service, the request parameters comprising indicia of a plurality of models and parameters for the models; retrieving user data comprising a set of indicia of recommendable resources associated with the customer identifier; routing the content request, request parameters and user data to a plurality of ranking and optimization component, each component generating a recommendation score for each recommendable resource; generating content recommendations based on the recommendation score which content recommendations are returned to the requesting user and stored by the server as a recommendation event within a repository of recommendation events; evaluating the relative efficacy of the one or more components, which models are returned to the requesting user and stored by the server as a recommendation event within a repository of recommendation events; evaluating the relative efficacy of the one or more components through continued usage; optimizing model efficacy by updating parameters within the parameter service based on the relative efficacy.