Display Content Selection Using Viewer Latent-Interest Feedback
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Solution Overview
Problem
Existing content display systems fail to accurately match displayed content with the latent interests of viewers, despite estimating attributes based on their appearances.
Innovation Solution
An information processing device and method that identifies third and fourth content with a lower relevance to first content based on viewer actions, allowing for the display of content that aligns with latent viewer interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content is selected based on viewer attributes estimated from appearance, then content matching viewer demographics can be displayed, but content matching latent interests of viewers cannot be displayed
Solution Approach 1:
The system displays test content (first and second content) before selecting final content to display. By preliminarily exposing viewers to multiple content options and measuring their viewing actions, the system gathers information about latent interests that cannot be obtained from appearance attributes alone. This preliminary action enables subsequent accurate content selection matching viewer preferences.
Solution Approach 2:
The system measures viewing actions (viewing time, attention level) as feedback signals to determine viewer interest in displayed content. This feedback mechanism allows the system to iteratively refine content selection by comparing actual viewer engagement with expected engagement based on attributes, thereby identifying and displaying content that truly matches latent interests.
2Productivity
If content with highest display desire is displayed in largest subarea, then most interesting content can be shown, but content based on latent interests cannot be displayed
Solution Approach 1:
The system dynamically adjusts content selection and display area allocation based on real-time viewing action measurements. Rather than statically assigning content based on attributes or simple popularity metrics, the system continuously adapts content display decisions by measuring actual viewer engagement and using this information to identify and promote content matching latent interests across different display subareas.
Solution Approach 2:
The system uses viewing action measurements as feedback to dynamically reassign content to display subareas. By monitoring which content generates genuine viewer engagement versus which content merely fills space, the system can optimize the distribution of content across subareas to maximize both display efficiency and alignment with latent viewer interests.
Data Source
AI summary
An information processing device includes a first display control unit configured to display together first content and second content, which is different from the first content, together, in a display area of a display unit. The information processing device further includes an identification unit configured to identify third content and fourth content on the basis of a viewing action for the first content and the second content. The information processing device further includes a second display control unit configured to display, in the display area, the third content as identified and the fourth content as identified. A degree of relevance between the third content and the fourth content is lower than a degree of relevance between the third content and the first content.