18458817. Ranking of Content Based On Implied Relationships simplified abstract (Apple Inc.)

Ranking of Content Based On Implied Relationships

Organization Name

Apple Inc.

Inventor(s)

Xiaoyuan Goodman Gu of San Jose CA (US)

Yuan Yen Tai of Pleasanton CA (US)

Moliang Zhou of Santa Clara CA (US)

Dayvid Victor Rodrigues De Oliveira of Round Rock TX (US)

Brian Knott of New York City NY (US)

Jin Cao of Ardsley NY (US)

Jia Huang of Mountain View CA (US)

Ranking of Content Based On Implied Relationships - A simplified explanation of the abstract

This abstract first appeared for US patent application 18458817 titled 'Ranking of Content Based On Implied Relationships

The present technology allows for establishing connections between content items that do not have direct relationships, using implicit influence relationships derived from various data sources.

• User download sequence data, campaign data with keyword targeting, and content review data mentioning other content can be used to establish influence relationships.
• Relevance of content items can be determined based on both influence relationships and similarity relationships with other content items.
• A context-driven factor is included to adjust the impact of influence relationships in ranking content items based on the parameters of relevance.
• The importance of influence relationships in ranking content items can vary depending on the context in which the content item is considered relevant.

Potential Applications: This technology can be applied in content recommendation systems, personalized marketing campaigns, and targeted advertising strategies.

Problems Solved: This technology addresses the challenge of establishing connections between content items that do not have explicit relationships, improving the accuracy of content recommendations and marketing campaigns.

Benefits: Enhanced relevance of content recommendations, improved targeting in marketing campaigns, and increased user engagement with content.

Commercial Applications: This technology can be utilized by content platforms, e-commerce websites, and digital marketing agencies to optimize content recommendations and advertising strategies.

Questions about the Technology: 1. How does the context-driven factor impact the ranking of content items based on influence relationships? 2. What are the key data sources used to establish implicit influence relationships in this technology?

Original Abstract Submitted

The present technology has the ability to establish connections between content that do not have direct or explicit relationships. Implicit influence relationships can be established from user download sequence data, campaign data with keyword targeting, and content review data that mentions other content. Using these influence relationships, the relevance of content items can be determined based on the influence relationship of linked content items and a similarity relationship of content items. However, the importance of the influence relationship in ranking content items can vary depending on the parameters against which the content item is considered relevant. To address this, the present technology includes a context-driven factor that is used as a weight to adjust the impact of the influence relationship of the ranking, depending on the parameters against which the content item is considered relevant.