Method and system for generating a linear machine learning model for predicting online user input actions

US8364627B2 · kind B2 · utility

Assignee

• YAHOO HOLDINGS, INC. · US

Inventors

• John Canny · Berkeley, US
• Shi Zhong · Lo Wu, CN
• Scott Gaffney · Palo Alto, US
• Chad Brower · Campbell, US
• Pavel Berkhin · Sunnyvale, US
• George H. John · Redwood City, US

Key dates

• Filing date: Jan 31, 2011
• Grant date: Jan 29, 2013
• Expiry date: Sep 11, 2031

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/02
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.