Interest Estimation Device Using Cognitive Bias Analysis
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Solution Overview
Problem
Existing technologies cannot effectively estimate a consumer's interest in a product based on their cognitive biases.
Innovation Solution
An interest estimation device that includes a storage unit for cognitive bias tendency information, an acquisition unit for user cognitive bias information, and an estimation unit that calculates the user's interest in content based on the stored and acquired information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cognitive bias information is used to estimate user interest, then estimation accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the interest estimation process into three functional modules: storage unit for cognitive bias tendency information, acquisition unit for user cognitive bias information, and estimation unit for calculating interest levels. This segmentation allows each component to perform a specific function, improving estimation accuracy while managing complexity through modular design.
Solution Approach 2:
Cognitive bias information serves as an intermediary element that bridges user characteristics and content interest estimation. By introducing this intermediate data layer, the system can estimate interest accuracy without requiring direct complex analysis of user behavior, thus improving measurement precision while controlling device complexity.
2Reliability
If cognitive bias tendency information is stored for multiple users, then estimation reliability is improved, but information storage requirements increase
Solution Approach 1:
The system extracts only the essential cognitive bias tendency information needed for interest estimation, storing it in a structured format in the storage unit. By taking out only the necessary data elements rather than storing complete user profiles, the system improves estimation reliability while minimizing data storage requirements.
Solution Approach 2:
The system transforms raw user data into condensed cognitive bias parameters that capture essential user characteristics. By changing the data representation from detailed user information to standardized cognitive bias parameters, the system maintains high estimation reliability while significantly reducing the quantity of stored information.
Data Source
AI summary
An object is to estimate interest of a user in a content on the basis of a cognitive bias of the user. An interest estimation device (1) includes a storage unit (11) that stores cognitive bias tendency information relating to a cognitive bias present in tendency of a user expressing interest in a predetermined content, an acquisition unit (10) that acquires user cognitive bias information relating to a cognitive bias of a target user who is a user to be targeted, and an estimation unit (13) that estimates interest of the target user in the content on the basis of the cognitive bias tendency information stored by the storage unit (11) and the user cognitive bias information acquired by the acquisition unit (10).