Ad Selection Logic for Viewer Attribute Matching
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Solution Overview
Problem
Existing information processing devices struggle to prevent an increase in display performance being biased toward specific advertisements while also ensuring that advertisements displayed are appropriate for the viewer's attributes.
Innovation Solution
An information processing device that acquires a captured image of a viewer, determines the viewer's attribute classification, and selects an advertisement based on display performance and reference values associated with each classification, ensuring that the selected advertisement does not exceed predetermined reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advertisement display selection is based solely on display performance metrics, then display performance bias toward specific advertisements is prevented, but advertisement appropriateness for viewer attributes deteriorates
Solution Approach 1:
The patent segments the advertisement selection process into multiple independent evaluation dimensions: display performance evaluation (first evaluation result) and viewer attribute matching evaluation (second evaluation result). Each dimension is assessed separately and then integrated to determine the final advertisement selection, preventing bias toward any single evaluation criterion.
Solution Approach 2:
The patent changes the selection parameters by introducing a dual-parameter evaluation system instead of relying on a single display performance metric. The first parameter evaluates display performance (preventing bias) while the second parameter evaluates viewer attribute matching (ensuring appropriateness), and the advertisement with the optimal combination of both parameters is selected.
2Adaptability or versatility
If advertisement selection prioritizes viewer attribute matching, then advertisement appropriateness for viewers is improved, but display performance balance deteriorates
Solution Approach 1:
The patent segments the advertisement selection process into multiple independent evaluation dimensions: display performance evaluation (first evaluation result) and viewer attribute matching evaluation (second evaluation result). Each dimension is assessed separately and then integrated to determine the final advertisement selection, preventing bias toward any single evaluation criterion.
Solution Approach 2:
The patent changes the selection parameters by introducing a dual-parameter evaluation system instead of relying on a single viewer attribute metric. The first parameter evaluates display performance (ensuring balance) while the second parameter evaluates viewer attribute matching (ensuring appropriateness), and the advertisement with the optimal combination of both parameters is selected.
Data Source
AI summary
Provided is an information processing device in which, in a case that at least a first person and a second person are included in a captured image, a second classification is selected when performing a first determination that involves determining that track record of a first advertisement which is an advertisement associated with a first classification determined by a determination unit with respect to an attribute of the first person exceeds a first reference value which is a reference value associated with a first classification and a second determination that involves determining that track record of a second advertisement which is an advertisement associated with the second classification determined by the determination unit with respect to an attribute of the second person does not exceed a second reference value which is a reference value associated with the second classification.