Recommender systems and methods using cascaded machine learning models

US11538086B2 · kind B2 · utility

Assignee

• Amadeus S.A.S. · FR

Inventors

• Benoit Lardeux · Valbonne, FR
• David Renaudie · Biot, FR
• Rodrigo Alejandro Acuna Agost · Golfe-Juan, FR
• Eoin THOMAS · Antibes, FR
• Mourad Boudia · Antibes, FR
• Papa Birame Sane · Vallauris, FR

Key dates

• Filing date: Oct 23, 2019
• Grant date: Dec 27, 2022
• Expiry date: Jun 23, 2040

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04L67/306
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Computer-implemented methods of providing personalized recommendations to a user of items available in an online system, and related systems. First-level features including context features are computed based upon context data. A first-level machine learning model is then evaluated using the first-level features to generate predictions of user behavior in relation to a plurality of individual items available via the online system. A list of proposed item recommendations is constructed based upon the predictions. Second-level features are computed based upon the context data and list features based upon the list of proposed item recommendations and the corresponding predictions generated by the first-level machine learning model. A second-level machine learning model is evaluated using the second-level features to generate a prediction of user behavior in relation to the list of proposed item recommendations. A personalized list of item recommendations is provided based upon the prediction generated by the second-level machine learning model.