Machine learning system for configuring social media campaigns

US11093979B2 · kind B2 · utility

Assignee

• Oracle International Corporation · US

Inventors

• Michael J. Strutton · Villa Rica, US
• John B. Nolt · Atlanta, US
• Chad Steven Estes · Atlanta, US
• Kimberly Ann Wolfe · Decatur, US
• Yizhou Jiang · Redwood City, US
• Natalie You · Mountain View, US
• Wenhua Li · Dongguan, CN
• Tara U. Roberts · Austin, US

Key dates

• Filing date: Jan 3, 2019
• Grant date: Aug 17, 2021
• Expiry date: Aug 21, 2039

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04L51/18
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Techniques for using machine learning to configure social media campaigns are disclosed. A social relationship management (SRM) service performs supervised machine learning to generate a learned model, at least by: generating feature vectors based on training data including campaign configuration data and one or more campaign success metrics; and performing pattern recognition on the feature vectors to determine one or more preferred campaign configurations. The SRM service publishes messages to one or more social media platforms and receives user interaction data associated with users' interactions with the messages. The SRM service performs unsupervised machine learning to update the learned model based at least in part on the user interaction data. The SRM service receives a request to configure a social media campaign, applies data associated with the request to the learned model to determine a preferred campaign configuration, and configures the social media campaign based on the preferred campaign configuration.